Papers by Ohad Ben-shahar
Journal of Vision, Sep 23, 2011
Springer eBooks, Aug 17, 2007
Vision Research, Mar 1, 2007
Studies of object-based attention (OBA) have suggested that attentional selection is intimately a... more Studies of object-based attention (OBA) have suggested that attentional selection is intimately associated with discrete objects. However, the relationship of this association to the basic visual features ('textons') which guide the segregation of visual scenes into 'objects' remains largely unexplored. Here we study this hypothesized relationship for one of the most conspicuous features of early vision: orientation. To do so we examine how attention spreads through uniform (one 'object') orientation-deWned textures (ODTs), and across texture-deWned boundaries in discontinuous (two 'objects') ODTs. Using the divided-attention paradigm we Wnd that visual events that are known to trigger orientation-based texture segregation, namely perceptual boundaries deWned by high orientation and/or curvature gradients, also induce a signiWcant cost on attentional selection. At the same time we show that no eVect is incurred by the absolute value of the textons, i.e., by the general direction (or, the 'grain') of the texture-in conXict with previous Wndings in the OBA literature. Collectively these experiments begin to reveal the link between object-based attention and texton-based segregation, a link which also oVers important cross-disciplinary methodological advantages.
arXiv (Cornell University), Aug 17, 2020
Jigsaw puzzle solving, the problem of constructing a coherent whole from a set of non-overlapping... more Jigsaw puzzle solving, the problem of constructing a coherent whole from a set of non-overlapping unordered visual fragments, is fundamental to numerous applications and yet most of the literature of the last two decades has focused thus far on less realistic puzzles whose pieces are identical squares. Here we formalize a new type of jigsaw puzzle where the pieces are general convex polygons generated by cutting through a global polygonal shape/image with an arbitrary number of straight cuts, a generation model inspired by the celebrated Lazy caterer's sequence. We analyze the theoretical properties of such puzzles, including the inherent challenges in solving them once pieces are contaminated with geometrical noise. To cope with such difficulties and obtain tractable solutions, we abstract the problem as a multi-body spring-mass dynamical system endowed with hierarchical loop constraints and a layered reconstruction process. We define evaluation metrics and present experimental results on both apictorial and pictorial puzzles to show that they are solvable completely automatically.
Journal of Vision, Oct 20, 2020
Journal of Vision, Oct 20, 2020
When a curved mirror-like surface moves relative to its environment, it induces a motion field-or... more When a curved mirror-like surface moves relative to its environment, it induces a motion field-or specular flow-on the image plane that observes it. This specular flow is related to the mirror's shape through a non-linear partial differential equation, and there is interest in understanding when and how this equation can be solved for surface shape. Existing analyses of this 'shape from specular flow equation' have focused on closed-form solutions, and while they have yielded insight, their critical reliance on externally-provided initial conditions and/or specific motions makes them difficult to apply in practice. This paper resolves these issues. We show that a suitable reparameterization leads to a linear formulation of the shape from specular flow equation. This formulation radically simplifies the reconstruction process and allows, for example, both motion and shape to be recovered from as few as two specular flows even when no externally-provided initial conditions are available. The result of our analysis is a practical method for recovering shape from specular flow that operates under arbitrary, unknown motions in unknown illumination environments and does not require additional shape information from other sources.
Like most animals, the survival of fish depends crucially on navigation in space. This capacity h... more Like most animals, the survival of fish depends crucially on navigation in space. This capacity has been documented in numerous behavioral studies that have revealed navigation strategies and the sensory modalities used for navigation. However, virtually nothing is known about how freely swimming fish represent space and locomotion in the brain to enable successful navigation. Using a novel wireless neural recording system, we measured the activity of single neurons in the goldfish lateral pallium, a brain region known to be involved in spatial memory and navigation, while the fish swam freely in a two-dimensional water tank. Four cell types were identified: border cells, head direction cells, speed cells and conjunction head direction with speed. Border cells were active when the fish was near the boundary of the environment. Head direction cells were shown to encode head direction. Speed cells only encoded the absolute speed independent of direction suggestive of an odometry signal. Finally, the conjunction of head direction with speed cells represented the velocity of the fish. This study thus sheds light on how information related to navigation is represented in the brain of swimming fish, and addresses the fundamental question of the neural basis of navigation in this diverse group of vertebrates. The similarities between our observations in fish and earlier findings in mammals may indicate that the networks controlling navigation in vertebrate originate from an ancient circuit common across vertebrates.
Journal of Real-time Image Processing, Mar 28, 2013
Visual tracking is considered a common procedure in many real-time applications. Such systems are... more Visual tracking is considered a common procedure in many real-time applications. Such systems are required to track objects under changes in illumination, dynamic viewing angle, image noise and occlusions (to name a few). But to maintain real-time performance despite these challenging conditions, tracking methods should require extremely low computational resources, therefore facing a trade-off between robustness and speed. Emergence of new consumer-level cameras capable of capturing video in 60 fps challenges this tradeoff even further. Unfortunately, state-of-the-art tracking techniques struggle to meet frame rates over 30 VGA-resolution fps with standard desktop power, let alone on typically-weaker mobile devices. In this paper we suggest a significantly cheaper computational method for tracking in colour video clips, that greatly improves tracking performance, in terms of robustness/speed trade-off. The suggested approach employs a novel similarity measure that explicitly combines appearance with object kinematics and a new adaptive Kalman filter extends the basic tracking to provide robustness to occlusions and noise. The linear time complexity of this method is reflected in computational efficiency and high processing rate. Comparisons with two recent trackers show superior tracking robustness at more than 5 times faster operation, all using naïve C/C?? implementation and built-in OpenCV functions.
Lecture Notes in Computer Science, 2002
Locally parallel dense patterns-sometimes called texture flowsdefine a perceptually coherent stru... more Locally parallel dense patterns-sometimes called texture flowsdefine a perceptually coherent structure which is important to image segmentation, edge classification, shading analysis, and shape interpretation. This paper develops the notion of texture flow from a geometrical point of view to argue that local measurements of such structures must incorporate two curvatures. We show how basic theoretical considerations lead to a unique model for the local behavior of the flow and allow for the specification of consistency constraints between nearby measurements. The computation of globally coherent structure via neighborhood relationships is demonstrated on synthetic and natural images, and is compared to orientation diffusion.
Journal of Vision, Oct 8, 2015
Visual pop-out is a phenomenon by which the latency to detect a target in a scene is independent ... more Visual pop-out is a phenomenon by which the latency to detect a target in a scene is independent of the number of other elements, the distractors. Pop-out is an effective visual-search guidance that occurs typically when the target is distinct in one feature from the distractors, thus facilitating fast detection of predators or prey. However, apart from studies on primates, pop-out has been examined in few species and demonstrated thus far in rats, archer fish, and pigeons only. To fill this gap, here we study pop-out in barn owls. These birds are a unique model system for such exploration because their lack of eye movements dictates visual behavior dominated by head movements. Head saccades and interspersed fixation periods can therefore be tracked and analyzed with a head-mounted wireless microcamera-the OwlCam. Using this methodology we confronted two owls with scenes containing search arrays of one target among varying numbers (15-63) of similar looking distractors. We tested targets distinct either by orientation (Experiment 1) or luminance contrast (Experiment 2). Search time and the number of saccades until the target was fixated remained largely independent of the number of distractors in both experiments. This suggests that barn owls can exhibit pop-out during visual search, thus expanding the group of species and brain structures that can cope with this fundamental visual behavior. The utility of our automatic analysis method is further discussed for other species and scientific questions.
Scientific Reports, Sep 8, 2020
Like most animals, the survival of fish depends on navigation in space. This capacity has been do... more Like most animals, the survival of fish depends on navigation in space. This capacity has been documented in behavioral studies that have revealed navigation strategies. However, little is known about how freely swimming fish represent space and locomotion in the brain to enable successful navigation. Using a wireless neural recording system, we measured the activity of single neurons in the goldfish lateral pallium, a brain region known to be involved in spatial memory and navigation, while the fish swam freely in a two-dimensional water tank. We found that cells in the lateral pallium of the goldfish encode the edges of the environment, the fish head direction, the fish swimming speed, and the fish swimming velocity-vector. This study sheds light on how information related to navigation is represented in the brain of fish and addresses the fundamental question of the neural basis of navigation in this group of vertebrates. Navigation is a fundamental behavioral capacity facilitating survival in many animal species 1-4. It involves the continuous estimation and representation of the animal's position and direction in the environment, which are implemented in the planning and execution of movements and trajectories towards target locations 5,6. Navigation has been extensively investigated in numerous taxa across the animal kingdom, but attempts to probe its neural substrate have mainly been focused on mammals 7 and insects 8. In mammals, neurons in the hippocampal formation encode information about the position and orientation of the animal in space 5-7,9,10. These cells include place cells 11 , grid cells 12 , head direction cells 13,14 , and other cell types 15,16. In insects, a ring-shaped neural network in the central complex of the fruit fly was shown to represent its heading direction 8. Teleost fish, which form the largest vertebrate class, have shown to have many high cognitive abilities with navigation among them 17-23. To better understand space representation in non-mammalian vertebrates, we explored the neural substrate of navigation in the goldfish (Carassius auratus) as a representative of the teleost class. These fish are known to be able to navigate by exploiting either an allocentric or an egocentric frame of reference 24. This may imply that the goldfish has the ability to build an internal representation of space in the form of a cognitive map 25. This would include cognitive map-like navigation strategies to find a goal when starting from an unfamiliar initial position or taking shorter alternative routes (shortcuts) when possible 25-28. Furthermore, goldfish integrate many environmental cues when navigating 29-31 ; therefore, a change of a single cue does not impair their navigation ability in known environment 27,29. Previous work by Canfield and Mizumori describe a method for extracellular recording system in tethered goldfish. Their paper provides preliminary evidence for speed and spatial encoding in the goldfish lateral pallium 32. In addition, lesion studies in goldfish have shown that the fish pallium, which is the dorsal part of the telencephalon, is crucial for spatial navigation. A lesion in the lateral areas of the pallium leads to impairment in allocentric spatial memory and learning, but not when the lesion affects other parts of the telencephalon 27. These findings are similar to results from lesions studies of the hippocampus in mammals and further strengthen the
Good continuation is a fundamental principle of perceptual organization that guides the grouping ... more Good continuation is a fundamental principle of perceptual organization that guides the grouping of parts based on how they should succeed one another within coherent wholes. Despite the general language that was used by the Gestalt psychologists in phrasing this principle, computational work has focused almost exclusively on the study of curve-like structures. Here we offer, for the first time, a rigorous generalization of good continuation to arbitrary visual structures that can be abstracted as scalar functions over the image plane. The differential geometry of these structures dictates that their good continuation should be based both on their value and on the geometry of their levelsets, which yield a coupled system of equations solvable for a formal model. We exhibit the resulting computation on shading and intensity functions, demonstrating how it eliminates spurious measurements while preserving both regular structure and singularities. Related implementations could be applied to color channels, motion magnitude, and disparity signals.
Lecture Notes in Computer Science, 2011
Active contours are used extensively in vision for more than two decades, primarily for applicati... more Active contours are used extensively in vision for more than two decades, primarily for applications such as image segmentation and object detection. The vast majority of active contours models make use of closed curves and the few that employ open curves rely on either fixed boundary conditions or no boundary conditions at all. In this paper we discuss a new class of open active contours with free boundary conditions, in which the end points of the open active curve are restricted to lie on two parametric boundary curves. We discuss how this class of curves may assist and facilitate various vision applications and we demonstrate its utility in applications such as boundary detection, feature tracking, and seam carving.
International journal of computer vision, Mar 22, 2024
Uploads
Papers by Ohad Ben-shahar