Active Vision

his paper is concerned with a computational solution for normal optical flow estimation using space-variant image sampling. The article describes one solution for the problem based on log-Tpol ar images, including the algorithm implementation on digital signal processing hardware. The log-polar structure achieves high data compressing rates by maintaining a high resolution area-the fovea-and a space-variant resolution-the retinal periphery. This sampling scheme enables the implementation of selective processing, characteristic of attentive vision. The solution was developed to be used with an active vision system to pursue moving objects, assuming that the cameras could also move. Some properties of the log-polar structure are also described and the main results of the implementation are presented.

In this paper, a basic conceptual architecture aimed at the design of Computer Vision System is qualitatively described. The proposed architecture addresses the design of vision systems in a modular fashion using modules with three distinct units or components: a processing network or diagnostics unit, a control unit and a communications unit. The control of the system at the modules level is designed based on a Discrete Events Model. This basic methodology has been used to design a real-time active vision system for detection, tracking and recognition of people. It is made up of three functional modules aimed at the detection, tracking, recognition of moving individuals plus a supervision module. The detection module is devoted to the detection of moving targets, using optic flow computation and relevant areas extraction. The tracking module uses an adaptive correlation technique to fixate on moving objects. The objective of this module is to pursuit the object, centering it into a relocatable focus of attention window (FOAW) to obtain a good view of the object in order to recognize it. Several focus of attention can be tracked simultaneously. The recognition module is designed in an opportunistic style in order to identify the object whenever it is possible. A demonstration system has been developed to detect, track and identify walking people. This research is sponsored in part by Spanish CICYT under project TAP95-0288.

This paper deals with the mechanical aspects of robot vision and focuses on the design and implementation of a high-performance system. The system is called CeDAR (Cable Drive Active vision Robot). As part of the research at the Robotic Systems Laboratory (RSL) to develop real-world vision systems, CeDAR is designed for speed and accuracy through its novel use of cables in zerobacklash transmissions and a parallel mechanical architecture. By optimising the design for agility, the system is able to a carry a large payload (700g) while achieving its performance specification of five 90°saccades per second with an angular repeatability of 0.01°in all three axes.

In this paper, the procedure developed to calibrate a whole-field optical profilometer and the evaluation of the measurement performance of the system are presented. The sensor is based on the projection of structured light and on active triangulation. The dependence of the measurements on the geometric parameters of the system is shown, as well as the criterion to calibrate the system. From the extensive set of experiments carried out to evaluate the measurement performance, good linearity has been observed, and an overall mean value of the measurement error equal to 40 m, with a variability of about 35 m has been estimated.

An approach to active vision based on information theory and statistical mechanics is presented. Density of entropy production measured along a spatio-chromatic diffusion of a colour image is used to build a conspicuity map of the image. The map is successively given as input to a dynamic neural network in order to drive a focus-of-attention scanpath

While it is true that SBM shapes and charts the direction of school operations, it is interesting to discuss how a developing country like the Philippines is influenced by this reform strategy as a structural and procedural framework in managing its system of education, particularly, its basic education sector which through the years has been criticized for its alarming state as shown by its performance indicators rates. This paper purports to provide a panorama on how school-based management as a restructuring framework is viewed and interpreted by the basic education sector which constitutes the largest portion of the country’s educational system. Specifically, the eight key elements of successful SBM schools, namely: (1) an active vision; (2) meaningful decision-making authority; (3) distribution of power; (4) development and use of knowledge and skills; (5) collecting and communicating information; (6) rewards for progress; (7) shared leadership; and (8) cultivating resources, were used to serve the purpose of this discourse.

In this paper we analyze in some detail the geometry of a pair of cameras, i.e. a stereo rig. Contrarily to what has been done in the past and is still done currently, for example in stereo or motion analysis, we do not assume that the intrinsic parameters of the cameras are known (coordinates of the principal points, pixels aspect ratio and focal lengths). This is important for two reasons. First, it is more realistic in applications where these parameters may v ary according to the task (active vision). Second, the general case considered here, captures all the relevant information that is necessary for establishing correspondences between two pairs of images. This information is fundamentally projective and is hidden in a confusing manner in the commonly used formalism of the Essential matrix introduced by Longuet-Higgins 40]. This paper clari es the projective nature of the correspondence problem in stereo and shows that the epipolar geometry can be summarized in one 3 3 matrix of rank 2 which w e propose to call the Fundamental matrix.

Localization is one of the most important basic skills of a mobile robot. Most approaches, however, still rely either on special sensors or require artificial environments. In this article, a novel approach is presented that can provide compass information for localization purely based on the visual appearance of a room. A robot using such a visual compass can quickly learn a cylindrical map of the environment, consisting of simple statistical features that can be computed very quickly. The visual compass algorithm is efficient, scalable and can therefore be used in real-time on almost any contemporary robotic platform. Extensive experiments on a Sony Aibo robot have validated that the approach works in a vast variety of environments.

The paper gives a survey on the new Expectationbased Multifocal Saccadic Vision (EMS-Vision) system for autonomous vehicle guidance developed at the Universität der Bundeswehr München (UBM). EMS-Vision is the third generation dynamic vision system following the 4-D approach. Its core element is a new camera arrangement, mounted on a high bandwidth pan-tilt head for active gaze control. Central knowledge representation and a hierarchical system architecture allow efficient activation and control of behavioral capabilities for perception and action. The system has been implemented on commercial off-the-shelf (COTS) hardware components in both UBM test vehicles VaMoRs and VaMP. Results from autonomous turnoff maneuvers, performed on army proving grounds, are discussed.

Can theories of mental imagery, conscious mental contents, developed within cognitive science throw light on the obscure (but culturally very significant) concept of imagination? Three extant views of mental imagery are considered: quasi-pictorial, description, and perceptual activity theories. The first two face serious theoretical and empirical difficulties. The third is (for historically contingent reasons) little known, theoretically underdeveloped, and empirically untried, but has real explanatory potential. It rejects the “traditional” symbolic computational view of mental contents, but is compatible with recent situated cognition and active vision approaches in robotics. This theory is developed and elucidated. Three related key aspects of imagination (non-discursiveness, creativity, and seeing as) raise difficulties for the other theories. Perceptual activity theory presents imagery as non-discursive and relates it closely to seeing as. It is thus well placed to be the basis for a general theory of imagination and its role in creative thought.

This paper describes the evolution of controllers for racing a simulated radio-controlled car around a track, modelled on a real physical track. Five different controller architectures were compared, based on neural networks, force fields and action sequences. The controllers use either egocentric (first person), Newtonian (third person) or no information about the state of the car (open-loop controller). The only controller that able to evolve good racing behaviour was based on a neural network acting on egocentric inputs.

We study visual servoing in a framework of detection and grasping of unknown objects. Classically, visual servoing has been used for applications where the object to be servoed on is known to the robot prior to the task execution. In addition, most of the methods concentrate on aligning the robot hand with the object without grasping it. In our work, visual servoing techniques are used as building blocks in a system capable of detecting and grasping unknown objects in natural scenes. We show how different visual servoing techniques facilitate a complete grasping cycle.

A method for evaluating, at video rate, the quality of actions for a single camera while mapping unknown indoor environments is presented. The strategy maximizes mutual information between measurements and states to help the camera avoid making ill-conditioned measurements that are appropriate to lack of depth in monocular vision systems. Our system prompts a user with the appropriate motion commands during 6-DOF visual simultaneous localization and mapping with a handheld camera. Additionally, the system has been ported to a mobile robotic platform, thus closing the control-estimation loop. To show the viability of the approach, simulations and experiments are presented for the unconstrained motion of a handheld camera and for the motion of a mobile robot with nonholonomic constraints. When combined with a path planner, the technique safely drives to a marked goal while, at the same time, producing an optimal estimated map.

Background and purpose Homonymous visual field defects (HVFDs) are among the most common disorders that occur in the elderly after vascular brain damage and can have a major impact on quality of life (QOL). Aims of this study were to describe the vision-targeted, health-related QOL in patients with HVFDs after cerebrovascular lesion, and to determine the relationship between patients' self-reported difficulties and the characteristics of HVFDs in the binocular visual field.

A high-resolution 3D model contains a wealth of information available for analysis. We can interactively examine features that are extremely small or only visible from 0272-1716/02/$17.00 Several projects target constructing dense 3D and appearance models of works of art or archaeological sites. We mention a few representative samples here. A group from IBM 1 used a combination of structured light 3D sensing and photometric stereo to model Michelangelo's Florentine Pietà. In a large-scale project initiated by Stanford University, 2 seven of Michelangelo's sculptures were modeled, as well as other artifacts including the parts of the Forma Urbis Romae. A European project called Esprit Archatour (EP9213)-see http://www.newcastle. research.ec.org/-digitized and modeled sculptures using active range sensing. The Italian National Research Council in Pisa, Italy, developed and demonstrated acquisition and processing systems dedicated to heritage. 3 A group from the University of Tokyo built shape and appearance models of the 15-meter bronze Great Buddha in Kamakura. 4 Another recent project 5 focused on Internet-transmittable 3D digital models of some architectural elements of the Roman Coliseum. 2. M. Levoy et al., "The Digital Michelangelo Project: 3D

Earlier , the biologically plausible active vision ,model for Multiresolutional Attentional Representation and Recognition (MARR) has been developed. The model is based on the scanpath theory of Noton and Stark 17 and provides invariant recognition of gray-level images. In the present paper, the algorithm of automatic image viewing trajectory formation in the MARR model, the results of psychophysical experiments, and possible applications of the model are considered. Algorithm of automatic image viewing trajectory formation is based on imitation of the scanpath formed by operator Several propositions about possible mechanisms for a consecutive selection of fixation points in human visual perception inspired by computer simulation results and known psyhophysical data have been tested and confirmed in our psychophysical experiments. In particular, we have found that gaze switch may be directed (i) to a peripheral part of the vision field which contains an edge oriented orthogonally to the edge in the point of fixation, and (ii) to a peripheral part of the vision field containing crossing edges. Our experimental results have been used to optimize automatic algorithm of image viewing in the MARR model. The modified model demonstrates an ability to recognize complex real world images invariantly with respect to scale, shift, rotation, illumination conditions, and, in part, to point of view and can be used to solve some robot vision tasks.

Manufacturers often express the performance of a 3D imaging device in various non-uniform ways for the lack of internationally recognized standard requirements for metrological parameters able to identify the capability of capturing a real scene. For this reason several national and international organizations in the last ten years have been developing protocols for verifying such performance. Ranging from VDI/VDE 2634, published by the Association of German Engineers and oriented to the world of mechanical 3D measurements (triangulation-based devices), to the ASTM technical committee E57, working also on laser systems based on direct range detection (TOF, Phase Shift, FM-CW, flash LADAR), this paper shows the state of the art about the characterization of active range devices, with special emphasis on measurement uncertainty, accuracy and resolution. Most of these protocols are based on special objects whose shape and size are certified with a known level of accuracy. By capturing the 3D shape of such objects with a range device, a comparison between the measured points and the theoretical shape they should represent is possible. The actual deviations can be directly analyzed or some derived parameters can be obtained (e.g. angles between planes, distances between barycenters of spheres rigidly connected, frequency domain parameters, etc.). This paper shows theoretical aspects and experimental results of some novel characterization methods applied to different categories of active 3D imaging devices based on both principles of triangulation and direct range detection.

In this article we present a neurally-inspired self-adaptive active binocular tracking scheme and an efficient mathematical model for online computation of desired binocular-head trajectories. The self-adaptive neural network (NN) model is general and can be adopted in output tracking schemes of any partly known robotic systems. The tracking scheme ingeniously combines the conventional Resolved Velocity Control (RVC) technique and an

In this paper a robust system for enabling robots to detect and identify humans in domestic environments is proposed. Robust human detection is achieved through the use of thermal and visual information sources that are integrated to detect human-candidate objects, which are further processed in order to verify the presence of humans and their identity using face information in the thermal and visual spectrums. Face detection is used to verify the presence of humans, and face recognition to identify them. Active vision mechanisms are employed in order to improve the relative pose of a candidate object/person in case direct identification is not possible. The response of the different modules is characterized, and the proposed system is validated using image databases of real domestic environments, and human detection and identification benchmarks of the RoboCup@Home research community.

In a surveillance system, a camera operator follows an object of interest by moving the camera, then gains additional information about the object by zooming. As the active vision field advances, the ability to automate such a system is nearing fruition. One hurdle limiting the use of object recognition algorithms in real-time systems is the quality of captured imagery; recognition algorithms often have strict scale and position requirements where if those parameters are not met, the performance rapidly degrades to failure. The goal of this work is to create a system that provides scale-invariant tracking using inexpensive off-the-shelf components.

Our work on active vision has recently focused on the computational modelling of navigational tasks, where our investigations were guided by the idea of approaching vision for behavioural systems in the form of modules that are directly related to perceptual tasks. These studies led us to branch in various directions and inquire into the problems that have to be addressed in order to obtain an overall understanding of perceptual systems. In this paper, we present our views about the architecture of vision systems, about how to tackle the design and analysis of perceptual systems, and promising future research directions. Our suggested approach for understanding behavioural vision to realize the relationships of perception and action builds on two earlier approaches, the Medusa philosophy' and the Synthetic approach*. The resulting framework calls for synthesizing an artificial vision system by studying vision competences of increasing complexity and, at the same time, pursuing the integration of the perceptual components with action and learning modules. We expect that computer vision research in the future will progress in tight collaboration with many other disciplines that are concerned with empirical approaches to vision, i.e. the understanding of biological vision. Throughout the paper, we describe biological findings that motivate computational arguments which we believe will influence studies of computer vision in the near future.

In recent years, active three-dimensional (3D) active vision systems or range cameras for short have come out of research laboratories to find niche markets in application fields as diverse as industrial design, automotive manufacturing, geomatics, space exploration and cultural heritage to name a few. Many publications address different issues link to 3D sensing and processing but currently these technologies pose a number of challenges to many recent users, i.e., "what are they, how good are they and how do they compare?". The need to understand, test and integrate those range cameras with other technologies, e.g. photogrammetry, CAD, etc. is driven by the quest for optimal resolution, accuracy, speed and cost. Before investing, users want to be certain that a given range camera satisfy their operational requirements. The understanding of the basic theory and best practices associated with those cameras are in fact fundamental to fulfilling the requirements listed above in an optimal way. This paper addresses the evaluation of active 3D range cameras as part of a study to better understand and select one or a number of them to fulfill the needs of industrial design applications. In particular, object material and surface features effect, calibration and performance evaluation are discussed. Results are given for six different range cameras for close range applications.

We present a new approach for tracking roads from satellite images, and thereby illustrate a general computational strategy (\active testing") for tracking 1D structures and other recognition tasks in computer vision. Our approach is related to recent work in active vision on \where to look next" and motivated by the \divide-and-conquer" strategy of parlor games such as \Twenty Questions." We choose \tests" (matched lters for short road segments) one at a time in order to remove as much uncertainty as possible about the \true hypothesis" (road position) given the results of the previous tests. The tests are chosen on-line based on a statistical model for the joint distribution of tests and hypotheses. The problem of minimizing uncertainty (measured by entropy) is formulated in simple and explicit analytical terms. To execute this entropy testing rule we then alternate between data collection and optimization: at each iteration new image data are examined and a new entropy minimization problem is solved (exactly), resulting in a new image location to inspect, and so forth. We report experiments using panchromatic SPOT satellite imagery with a ground resolution of ten meters: given a starting point and starting direction, we are able to rapidly track highways in southern France over distances on the order of one hundred kilometers without manual intervention.

Projectors are increasingly being used as lightsources in computer vision applications. In several applications, they are modeled as point light sources, thus ignoring the effects of illumination defocus. In addition, most active vision techniques assume that a scene point is illuminated only directly by the light source, thus ignoring global light transport effects. Since both defocus and global illumination co-occur in virtually all scenes illuminated by projectors, ignoring them can result in strong, systematic biases in the recovered scene properties. To make computer vision techniques work for general real world scenes, it is thus important to account for both these effects.

The empirical investigation of cognitive processes in infants is hampered by the limited development of their body and motor control skills. Novel gaze-contingent paradigms, where infants control their environment with their eyes, offer a solution to this problem since the control of gaze develops very early. Recently such a paradigm has been used to investigate the learning of anticipatory behaviour of 6/8-months-old infants in an experiment where gazing at a ``button'' causes the appearance of an interesting image.
The experiment shows that infants learn in few trials to ``press the button'' with their gaze and, remarkably, to anticipate the image appearance.
The experiment raises two questions:
(a) what are the processes supporting such fast learning?
(b) why does the anticipatory behaviour emerge?
This paper presents a bio-inspired model that puts forward possible answers to these questions.
The model consists of:
(a) a bottom-up attention component for scene saliency detection;
(b) a top-down attention component that uses reinforcement learning (RL) to learn to control gaze based on current foveal stimuli;
(c) a dynamic field map that decides where to look based on the bottom-up and top-down information.
The results show that the model is indeed capable of learning to perform anticipatory saccades in few trials.
The analysis of the system shows that this fast learning is due to the guidance exerted by the bottom-up component on the learning process of the top-down component.
Moreover, it shows that the anticipatory behaviour can be explained in terms of the action of the top-down component exploiting the learned spatial relations of stimuli in an anticipatory fashion.
Overall, the results indicate that the model has the essential features to theoretically frame, interpret, and design experiments based on the gaze-contingent paradigm.

The European Space Agency (ESA) is preparing for unmanned and/or manned exploration of several planets including Mercury and Mars. To support this endeavour several key technologies have to be developed. Among these necessary technologies are navigation sensors that can support landing and sample-return capsule rendezvous operations. A vision-based navigation sensor is currently being developed by ESA [1] which will enable surface relative navigation. The Planet and Asteroid Natural-scene Generation Utility (PANGU) is a system for generating simulated surfaces of planets and for producing images of those surfaces from specified camera positions and orientations [2][3][4][5][6][7]. PANGU was implemented specifically to support the development of vision-based navigation sensors and is now being used to validate associated image feature tracking algorithms. Vision-based sensors that use passive vision are only suitable for a landing on the sunlit side of a planet, unless the spacecraft contains an illumination source. Active vision sensors, particularly LIDAR, are suitable for lander navigation on the sunlit or dark side of a planet. They are also suitable for use on dimly sunlit objects such as asteroids. The planetary surfaces generated by PANGU are ideal for supporting the development and testing of LIDAR sensors and related signal processing techniques. In this case the camera model within PANGU that provides images of the surface is replaced by a LIDAR sensor model. This paper describes current research at the University of Dundee which is extending the capabilities of the PANGU tool to include LIDAR simulation. Effort is focused on the landing and rendezvous phases of planetary missions and the use of LIDAR to support the GNC function during these dangerous parts of the mission.

Our robotics group has teams in three leagues: Humanoid, Standard Platform League (SPL), and @Home. Taking advantage of this, we want to contribute to the transfer of relevant developments between the different RoboCup leagues. This year our new developments for the two-legged SPL include: (i) a new methodology for designing fall sequences with low impact in the robot joints, (ii) the proposition of new methodologies to be used in the vision system of our robots (task oriented active vision and context-based perception), (iii) the development of an omnidirectional gait for the Nao humanoid robots, and (iv) the development of an automated referee for the league, which uses a completely autonomous service robot as referee. In addition, a large amount of our efforts have been dedicated to the software adaptation of our control library, originally designed for AIBO robots, to the new Nao humanoid robots. Furthermore, we have depeloped a new robot control library that is platform independent.

This paper presents a vision system that ®nds and measures the location of 3D structures with respect to a CAD-model. The integration of a CAD-model to visual measurement and direct feedback of measurement results to the CAD is a key aspect. For the extraction of basic visual cues, independent and complementary modules are envisaged. The goal is that of navigating a legged robot into a ship structure using the pose estimated from visual landmarks extracted from the CAD-model. These are tracked in real-time by the vision system and are matched to the CAD-model. For the implementation of the vision system, commercial off-the-shelf parts were used along with a custom designed robot stereo head. The communication with other modules is done using simple ASCII commands on a ®ber channel network with standard TCP/IP protocol. This allows easy debugging, straightforward development of applications software with little effort, and very high data rates. q

This dissertation describes a new approach to visual tracking for monocular and binocular image sequences, and for both passive and active cameras. The method combines Kalman-type prediction with steepest-descent search for correspondences, using 2-dimensional affine mappings ...

We describe an evolutionary approach to active vision systems for dynamic feature selection. After summarizing recent work on evolution of a simulated active retina for complex shape discrimination, we describe in detail experiments that extend this approach to an all-terrain mobile robot equipped with a mobile camera. We show that evolved robots are capable of selecting simple visual features and actively maintaining them on the same retinal position, which largely simplifies the "recognition" task, in order to generate efficient navigation trajectories with an extremely simple neural control system. Analysis of evolved solutions indicates that robots develop a simple and yet very efficient version of edge detection and visual looming to detect obstacles and move away from them. Two evolved sensory-motor strategies are described, one where the mobile camera is actively used throughout the entire navigation and one where it is used only at the beginning to point towards relevant environmental features. The relationship between these two strategies are discussed in the context of the underlying visuomotor mechanisms and of the evolutionary conditions.

In this paper, the control problem of camera-in-hand robotic systems is considered. In this approach, a camera is mounted on the robot, usually at the hand, which provides an image of objects located in the robot environment. The aim of this approach is to move the robot arm in such a way that the image of the objects attains the desired locations. We propose a simple image-based direct visual servo controller which requires knowledge of the objects' depths, but it does not need to use the inverse kinematics and the inverse Jacobian matrix. By invoking the Lyapunov direct method, we show that the overall closed-loop system is stable and, under mild conditions on the Jacobian, local asymptotic stability is guaranteed. Experiments with a two degrees-of-freedom direct-drive manipulator are presented to illustrate the controller's performance.

Vergence provides robot vision systems with a crucial degree of freedom: it enables fixation of points in visual space at different distances from the observer. Vergence control, therefore, affects the performance of the stereo system as well as the results of motion estimation and tracking and, as such, must satisfy different requirements in order to be able to provide not only a stable fixation, but a stable binocular fusion, and a fast, smooth and accurate reaction to changes in the environment. To obtain this kind of performance the paper focuses specifically on the use of dynamic visual information to drive vergence control. In this context, moreover, the use of a space-variant, anthropomorphic sensor is described and some advantages in relation to vergence control are discussed to demonstrate the relevance of image plane geometry for this particular task. Expansion or contraction patterns and the temporal evolution of the degree of fusion measured in the log-polar domain are the inputs to the vergence control system and determine robust and accurate steering of the two cameras. Real-time experiments are presented to demonstrate the performance of the system covering different key situations.

We address the problem of online path planning for optimal sensing with a mobile robot. The objective of the robot is to learn the most about its pose and the environment given time constraints. We use a POMDP with a utility function that depends on the belief state to model the finite horizon planning problem. We replan as the robot progresses throughout the environment. The POMDP is highdimensional, continuous, non-differentiable, nonlinear, non-Gaussian and must be solved in real-time. Most existing techniques for stochastic planning and reinforcement learning are therefore inapplicable. To solve this extremely complex problem, we propose a Bayesian optimization method that dynamically trades off exploration (minimizing uncertainty in unknown parts of the policy space) and exploitation (capitalizing on the current best solution). We demonstrate our approach with a visually-guide mobile robot. The solution proposed here is also applicable to other closelyrelated domains, including active vision, sequential experimental design, dynamic sensing and calibration with mobile sensors.

This paper presents a new stereo sensor for active vision. Its cameras are mounted on two independent 2-DOF manipulators, themselves mounted on two translation stages. The system is designed for fast and accurate dynamical adjustments of gaze, vergence, and baseline. A complete description of its software and hardware components is given, including a detailed discussion of its calibration procedure. The performance of the sensor with respect to dynamical properties and measurement accuracy is also demonstrated through both simulations and experiments.

This material is presented to ensure timely dissemination of scholarly and technical work. Abstract -This paper presents a new approach dealing with virtual exploratory navigation inside vascular structures. It is based on the notion of active vision in which only visual perception drives the motion of the virtual angioscope. The proposed fly-through approach does not require a premodeling of the volume dataset or an interactive control of the virtual sensor during the fly-through. Active navigation combines the on-line computation of the scene view and its analysis, to automatically define the 3D sensor path. The navigation environment and the camera-like model are first sketched. The basic stages of the active navigation framework are then described: the virtual image computation (based on ray casting), the scene analysis process (using depth map), the navigation strategy and the virtual path estimation. Experimental results obtained from phantom model and patient CT-data are finally reported. Index Terms-virtual angioscopy, active virtual sensor, automatic path planning I. INTRODUCTION he recent advances in medical imaging (e.g. high resolution patient data), the availability of methods for image analysis and computer graphics, the technological resources provided by micro-devices and the design of minimal access surgical procedures have opened the road to new concepts. Virtual endoscopy represents one of these areas and points out the applicative potential of three dimensional (3D) imaging. It leads to less invasive diagnosis and therapeutic achievements, and addresses important issues in computer aided diagnosis, interventional planning, and medical education. Volumes provided by CT or MRI allow the user to move virtually within the anatomical structures. Different approaches addressing various clinical applications, such as virtual colonoscopy [1]-[7], virtual bronchoscopy [8]-). M. E. Bellemare was with LTSI, Rennes, France. He is now with LSIS,

During natural viewing, the eyes are never still. Even during fixation, miniature movements of the eyes move the retinal image across tens of foveal photoreceptors. Most theories of vision implicitly assume that the visual system ignores these movements and somehow overcomes the resulting smearing. However, evidence has accumulated to indicate that fixational eye movements cannot be ignored by the visual system if fine spatial details are to be resolved. We argue that the only way the visual system can achieve its high resolution given its fixational movements is by seeing via these movements. Seeing via eye movements also eliminates the instability of the image, which would be induced by them otherwise. Here we present a hypothesis for vision, in which coarse details are spatially encoded in gaze-related coordinates, and fine spatial details are temporally encoded in relative retinal coordinates.The temporal encoding presented here achieves its highest resolution by encoding along the elongated axes of simple-cell receptive fields and not across these axes as suggested by spatial models of vision. According to our hypothesis, fine details of shape are encoded by inter-receptor temporal phases, texture by instantaneous intra-burst rates of individual receptors, and motion by inter-burst temporal frequencies.

ABSTRACT Manufacturers often express the performance of a 3D imaging device in various non-uniform ways for the lack of internationally recognized standard requirements for metrological parameters able to identify the capability of capturing a real scene. For this reason several national and international organizations in the last ten years have been developing protocols for verifying such performance. Ranging from VDI/VDE 2634, published by the Association of German Engineers and oriented to the world of mechanical 3D measurements (triangulation-based devices), to the ASTM technical committee E57, working also on laser systems based on direct range detection (TOF, Phase Shift, FM-CW, flash LADAR), this paper shows the state of the art about the characterization of active range devices, with special emphasis on measurement uncertainty, accuracy and resolution. Most of these protocols are based on special objects whose shape and size are certified with a known level of accuracy. By capturing the 3D shape of such objects with a range device, a comparison between the measured points and the theoretical shape they should represent is possible. The actual deviations can be directly analyzed or some derived parameters can be obtained (e.g. angles between planes, distances between barycenters of spheres rigidly connected, frequency domain parameters, etc.). This paper shows theoretical aspects and experimental results of some novel characterization methods applied to different categories of active 3D imaging devices based on both principles of triangulation and direct range detection.

where he is currently an assistant professor. In 1986, he was a research assistant at the Department of Computer Science of Trinity College, Dublin, Ireland, where he was developing a system for the analysis of image data primarily aimed at the investigation of low-level visual proceses. In 1989, he was a visiting scientist at Thinking Machines Co. developing parallel algorithms for dynamic image processing on the Connection Machine. Dr. Tistarelli's research interests include robotics, computer vision (particularly in the area of three-dimensional and dynamic scene analysis), image processing, and artificial intelligence.