Visual Search and Exploration

Art exploration is a complex process conditioned by factors at different levels and includes both basic visual principles and complex cognitive factors. The human figure is considered a critical factor attracting the attention in art painting. Using an eye-tracking methodology, the goal of this study was to explore different elements of the human figure performing an action (face and body parts in action) in complex social scenes characterized by different levels of social interaction between agents depicted in scenes (individual vs. social). The sample included 44 laypersons, and the stimuli consisted of 10 fine art paintings representing the figurative style of classical art. The results revealed different scanning patterns of the human figure elements related to the level of social interaction of agents depicted in the scene. The agents' face attracted eye movements in social interaction scenes while the agents' body parts attracted eye movements only when the agents were involved in individual actions. These processes were confirmed specifically in participants with high empathic abilities who became immediately fixated on faces to develop a mimetic engagement with other agents. Future studies integrating other measures would help confirm the results obtained and strengthen their implication for embodiment processes.

Art exploration is a complex process conditioned by factors at different levels and includes both basic visual principles and complex cognitive factors. The human figure is considered a critical factor attracting the attention in art painting. Using an eye-tracking methodology, the goal of this study was to explore different elements of the human figure performing an action (face and body parts in action) in complex social scenes characterized by different levels of social interaction between agents depicted in scenes (individual vs. social). The sample included 44 laypersons, and the stimuli consisted of 10 fine art paintings representing the figurative style of classical art. The results revealed different scanning patterns of the human figure elements related to the level of social interaction of agents depicted in the scene. The agents' face attracted eye movements in social interaction scenes while the agents' body parts attracted eye movements only when the agents were involved in individual actions. These processes were confirmed specifically in participants with high empathic abilities who became immediately fixated on faces to develop a mimetic engagement with other agents. Future studies integrating other measures would help confirm the results obtained and strengthen their implication for embodiment processes.

Art exploration is a complex process conditioned by factors at different levels and includes both basic visual principles and complex cognitive factors. The human figure is considered a critical factor attracting the attention in art painting. Using an eye-tracking methodology, the goal of this study was to explore different elements of the human figure performing an action (face and body parts in action) in complex social scenes characterized by different levels of social interaction between agents depicted in scenes (individual vs. social). The sample included 44 laypersons, and the stimuli consisted of 10 fine art paintings representing the figurative style of classical art. The results revealed different scanning patterns of the human figure elements related to the level of social interaction of agents depicted in the scene. The agents' face attracted eye movements in social interaction scenes while the agents' body parts attracted eye movements only when the agents were involved in individual actions. These processes were confirmed specifically in participants with high empathic abilities who became immediately fixated on faces to develop a mimetic engagement with other agents. Future studies integrating other measures would help confirm the results obtained and strengthen their implication for embodiment processes.

Art exploration is a complex process conditioned by factors at different levels and includes both basic visual principles and complex cognitive factors. The human figure is considered a critical factor attracting the attention in art painting. Using an eye-tracking methodology, the goal of this study was to explore different elements of the human figure performing an action (face and body parts in action) in complex social scenes characterized by different levels of social interaction between agents depicted in scenes (individual vs. social). The sample included 44 laypersons, and the stimuli consisted of 10 fine art paintings representing the figurative style of classical art. The results revealed different scanning patterns of the human figure elements related to the level of social interaction of agents depicted in the scene. The agents' face attracted eye movements in social interaction scenes while the agents' body parts attracted eye movements only when the agents were involved in individual actions. These processes were confirmed specifically in participants with high empathic abilities who became immediately fixated on faces to develop a mimetic engagement with other agents. Future studies integrating other measures would help confirm the results obtained and strengthen their implication for embodiment processes.

Visual search tasks have often been used to investigate how cognitive processes change with expertise. Several studies have shown visual experts' advantages in detecting objects related to their expertise. Here, we tried to extend these findings by investigating whether professional search experience could boost top-down monitoring processes involved in visual search, independently of advantages specific to objects of expertise. To this aim, we recruited a group of quality-control workers employed in citrus farms. Given the specific features of this type of job, we expected that the extensive employment of monitoring mechanisms during orange selection could enhance these mechanisms even in search situations in which orange-related expertise is not suitable. To test this hypothesis, we compared performance of our experimental group and of a well-matched control group on a computerized visual search task. In one block the target was an orange (expertise target) while in the other ...

According to the direct matching hypothesis, perceived movements automatically activate existing motor components through matching of the perceived gesture and its execution. The aim of the present study was to test the direct matching hypothesis by assessing whether visual exploration behavior correlate with deficits in gestural imitation in left hemisphere damaged (LHD) patients. Eighteen LHD patients and twenty healthy control subjects took part in the study. Gesture imitation performance was measured by the test for upper limb apraxia (TULIA). Visual exploration behavior was measured by an infrared eyetracking system. Short videos including forty gestures (20 meaningless and 20 communicative gestures) were presented. Cumulative fixation duration was measured in different regions of interest (ROIs), namely the face, the gesturing hand, the body, and the surrounding environment. Compared to healthy subjects, patients fixated significantly less the ROIs comprising the face and the gesturing hand during the exploration of emblematic and tool-related gestures. Moreover, visual exploration of tool-related gestures significantly correlated with tool-related imitation as measured by TULIA in LHD patients. Patients and controls did not differ in the visual exploration of meaningless gestures, and no significant relationships were found between visual exploration behavior and the imitation of emblematic and meaningless gestures in TULIA. The present study thus suggests that altered visual exploration may lead to disturbed imitation of tool related gestures, however not of emblematic and meaningless gestures. Consequently, our findings partially support the direct matching hypothesis.

Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context. Context, in its turn, is given by attributes associated with graph elements, such as individual nodes, edges, and groups of edges, as well as by the nature of the connections between individuals. In most systems, attributes of individuals and communities are not taken into consideration during graph layout, except to derive weights for force-based placement strategies. This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings. These properties are employed to layout nodes on the plane via multidimensional projection techniques. For the attribute mapping, we show that node proximity in the layout corresponds to similarity in attribute, leading to easiness in locating similar groups of nodes. The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm, reaching a meaningful layout in one pass. When a force algorithm is then applied to this initial mapping, the final layout presents better properties than conventional force-based approaches. Numerical evaluations show a number of advantages of pre-mapping points via projections. User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone. In order to allow better space usage for complex networks, a graph mapping on the surface of a sphere is also implemented.

Art exploration is a complex process conditioned by factors at different levels and includes both basic visual principles and complex cognitive factors. The human figure is considered a critical factor attracting the attention in art painting. Using an eye-tracking methodology, the goal of this study was to explore different elements of the human figure performing an action (face and body parts in action) in complex social scenes characterized by different levels of social interaction between agents depicted in scenes (individual vs. social). The sample included 44 laypersons, and the stimuli consisted of 10 fine art paintings representing the figurative style of classical art. The results revealed different scanning patterns of the human figure elements related to the level of social interaction of agents depicted in the scene. The agents' face attracted eye movements in social interaction scenes while the agents' body parts attracted eye movements only when the agents were involved in individual actions. These processes were confirmed specifically in participants with high empathic abilities who became immediately fixated on faces to develop a mimetic engagement with other agents. Future studies integrating other measures would help confirm the results obtained and strengthen their implication for embodiment processes.

Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context. Context, in its turn, is given by attributes associated with graph elements, such as individual nodes, edges, and groups of edges, as well as by the nature of the connections between individuals. In most systems, attributes of individuals and communities are not taken into consideration during graph layout, except to derive weights for force-based placement strategies. This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings. These properties are employed to layout nodes on the plane via multidimensional projection techniques. For the attribute mapping, we show that node proximity in the layout corresponds to similarity in attribute, leading to easiness in locating similar groups of nodes. The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm, reaching a meaningful layout in one pass. When a force algorithm is then applied to this initial mapping, the final layout presents better properties than conventional force-based approaches. Numerical evaluations show a number of advantages of pre-mapping points via projections. User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone. In order to allow better space usage for complex networks, a graph mapping on the surface of a sphere is also implemented.

Data exploration and visualization systems are of great importance in the Big Data era. Exploring and visualizing very large datasets has become a major research challenge, of which scalability is a vital requirement. In this survey, we describe the major prerequisites and challenges that should be addressed by the modern exploration and visualization systems. Considering these challenges, we present how state-of-the-art approaches from the Database and Information Visualization communities attempt to handle them. Finally , we survey the systems developed by Semantic Web community in the context of the Web of Linked Data, and discuss to which extent these satisfy the contemporary requirements.

Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context. Context, in its turn, is given by attributes associated with graph elements, such as individual nodes, edges, and groups of edges, as well as by the nature of the connections between individuals. In most systems, attributes of individuals and communities are not taken into consideration during graph layout, except to derive weights for force-based placement strategies. This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings. These properties are employed to layout nodes on the plane via multidimensional projection techniques. For the attribute mapping, we show that node proximity in the layout corresponds to similarity in attribute, leading to easiness in locating similar groups of nodes. The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm, reaching a meaningful layout in one pass. When a force algorithm is then applied to this initial mapping, the final layout presents better properties than conventional force-based approaches. Numerical evaluations show a number of advantages of pre-mapping points via projections. User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone. In order to allow better space usage for complex networks, a graph mapping on the surface of a sphere is also implemented.

Visual analysis of social networks is usually based on graph drawing algorithms and tools. However, social networks are a special kind of graph in the sense that interpretation of displayed relationships is heavily dependent on context. Context, in its turn, is given by attributes associated with graph elements, such as individual nodes, edges, and groups of edges, as well as by the nature of the connections between individuals. In most systems, attributes of individuals and communities are not taken into consideration during graph layout, except to derive weights for force-based placement strategies. This paper proposes a set of novel tools for displaying and exploring social networks based on attribute and connectivity mappings. These properties are employed to layout nodes on the plane via multidimensional projection techniques. For the attribute mapping, we show that node proximity in the layout corresponds to similarity in attribute, leading to easiness in locating similar groups of nodes. The projection based on connectivity yields an initial placement that forgoes force-based or graph analysis algorithm, reaching a meaningful layout in one pass. When a force algorithm is then applied to this initial mapping, the final layout presents better properties than conventional force-based approaches. Numerical evaluations show a number of advantages of pre-mapping points via projections. User evaluation demonstrates that these tools promote ease of manipulation as well as fast identification of concepts and associations which cannot be easily expressed by conventional graph visualization alone. In order to allow better space usage for complex networks, a graph mapping on the surface of a sphere is also implemented.

d a b e f c g Figure 1: Exploration of the InfoVis 2004 Contest co-authorship dataset using GraphDice. On the left is the main visualization window of GraphDice including (a) an overview plot matrix, (b) a selection history tool, (c) a selection query window, (d) a main plot, and (e) a toolbar. Overlapping nodes in the main plot are drawn using jitter (visible in the yellow selection query).