The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
Hiroshi Ishiguro - One of the best experts on this subject based on the ideXlab platform.
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integrating a Perceptual Information infrastructure with robotic avatars a framework for tele existence
Intelligent Robots and Systems, 1999Co-Authors: Hiroshi Ishiguro, Mohan M TrivediAbstract:Describes an infrastructural framework to support interactivity among entities that are not residing in the same physical environment. In such an environment, mobile robots supported by a Perceptual Information infrastructure gather Information and communicate with people in a distant place instead of the users. This is one of the possible and promising applications of robots based on the current technologies of robotics, multimedia and computer networks. The paper describes the overall architecture and main system components. We discuss experimental studies where underlying concepts and algorithms are evaluated.
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IROS - Integrating a Perceptual Information infrastructure with robotic avatars: a framework for tele-existence
Proceedings 1999 IEEE RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and, 1999Co-Authors: Hiroshi Ishiguro, Mohan M TrivediAbstract:Describes an infrastructural framework to support interactivity among entities that are not residing in the same physical environment. In such an environment, mobile robots supported by a Perceptual Information infrastructure gather Information and communicate with people in a distant place instead of the users. This is one of the possible and promising applications of robots based on the current technologies of robotics, multimedia and computer networks. The paper describes the overall architecture and main system components. We discuss experimental studies where underlying concepts and algorithms are evaluated.
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Robots Integrated with Environments - A Perceptual Information Infrastructure for robot navigation -
1998Co-Authors: Hiroshi IshiguroAbstract:This paper proposes a Perceptual Information In frastructure which supports robots in a real world and realizes real-time and robust robot navigation. One of the examples is a distributed vision system consisting of multiple vision agents and a com puter network for the agent communication. The design policies and experimental results for mo bile robot navigation are shown. The Perceptual Information infrastructure enables to develop a new research direction of robotics in which robots are considered as integrated systems with envi ronments. In addition to the infrastructure for robots, this paper discusses research issues which should be considered in order to develop the new intelligent robot systems.
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Robots Integrated with Environments
Robotics Research, 1998Co-Authors: Hiroshi IshiguroAbstract:This paper proposes a Perceptual Information Infrastructure which supports robots in a real world and realizes real-time and robust robot navigation. One of the examples is a distributed vision system consisting of multiple vision agents and a computer network for the agent communication. The design policies and experimental results for mobile robot navigation are shown. The Perceptual Information infrastructure enables to develop a new research direction of robotics in which robots are considered as integrated systems with environments. In addition to the infrastructure for robots, this paper discusses research issues which should be considered in order to develop the new intelligent robot systems.
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distributed vision system a Perceptual Information infrastructure for robot navigation
International Joint Conference on Artificial Intelligence, 1997Co-Authors: Hiroshi IshiguroAbstract:This paper proposes a Distributed Vision System as a Perceptual Information Infrastructure for robot navigation in a dynamically changing world. The distributed vision system, consisting of vision agents connected with a computer network, monitors the environment, maintains the environment models, and actively provides various Information for the robots by organizing communication between the vision agents. In addition to conceptual discussions and fundamental issues, this paper provides a prototype of the distributed vision system for navigating mobile robots.
Andrew D Wilson - One of the best experts on this subject based on the ideXlab platform.
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Perceptual Information supports transfer of learning in coordinated rhythmic movement
Psychological Research, 2020Co-Authors: Daniel Leach, Zoe Kolokotroni, Andrew D WilsonAbstract:In this paper, we trained people to produce 90° mean relative phase using task-appropriate feedback and investigated whether and how that learning transfers to other coordinations. Past work has failed to find transfer of learning to other relative phases, only to symmetry partners (identical coordinations with reversed lead–lag relationships) and to other effector combinations. However, that research has all trained people using transformed visual feedback (visual metronomes, Lissajous feedback) which removes the relative motion Information typically used to produce various coordinations (relative direction, relative position; Wilson and Bingham, in Percept Psychophys 70(3):465–476, 2008). Coordination feedback (Wilson et al., in J Exp Psychol Hum Percept Perform 36(6):1508, 2010) preserves that Information and we have recently shown that relative position supports transfer of learning between unimanual and bimanual performance of 90° (Snapp-Childs et al., in Exp Brain Res 233(7), 2225–2238, 2015). Here, we ask whether that Information can support the production of other relative phases. We found large, asymmetric transfer of learning bimanual 90° to bimanual 60° and 120°, supported by Perceptual learning of relative position Information at 90°. For learning to transfer, the two tasks must overlap in some critical way; this is additional evidence that this overlap must be Informational. We discuss the results in the context of an ecological, task dynamical approach to understanding the nature of perception–action tasks.
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Perceptual Information supports transfer of learning in coordinated rhythmic movement.
Psychological Research-psychologische Forschung, 2020Co-Authors: Daniel Peter Leach, Zoe Kolokotroni, Andrew D WilsonAbstract:In this paper, we trained people to produce 90 degrees mean relative phase using task-appropriate feedback and investigated whether and how that learning transfers to other coordinations. Past work has failed to find transfer of learning to other relative phases, only to symmetry partners (identical coordinations with reversed lead-lag relationships) and to other effector combinations. However, that research has all trained people using transformed visual feedback (visual metronomes, Lissajous feedback) which removes the relative motion Information typically used to produce various coordinations (relative direction, relative position; Wilson and Bingham, in Percept Psychophys 70(3):465-476, 2008). Coordination feedback (Wilson et al., in J Exp Psychol Hum Percept Perform 36(6):1508, 2010) preserves that Information and we have recently shown that relative position supports transfer of learning between unimanual and bimanual performance of 90 degrees (Snapp-Childs et al., in Exp Brain Res 233(7), 2225-2238, 2015). Here, we ask whether that Information can support the production of other relative phases. We found large, asymmetric transfer of learning bimanual 90 degrees to bimanual 60 degrees and 120 degrees , supported by Perceptual learning of relative position Information at 90 degrees . For learning to transfer, the two tasks must overlap in some critical way; this is additional evidence that this overlap must be Informational. We discuss the results in the context of an ecological, task dynamical approach to understanding the nature of perception-action tasks.
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Perceptual Information Supports Transfer of Learning in Coordinated Rhythmic Movement
2019Co-Authors: Daniel Peter Leach, Zoe Kolokotroni, Andrew D WilsonAbstract:In this paper, we trained people to produce 90° mean relative phase using task-appropriate feedback and investigated whether and how that learning transfers to other coordinations. Past work has failed to find transfer of learning to other relative phases, only to symmetry partners (identical coordinations with reversed lead-lag relationships) and to other effector combinations. However, that research has all trained people using transformed visual feedback (visual metronomes, Lissajous feedback) which removes the relative motion Information typically used to produce various coordinations (relative direction, relative position; Wilson & Bingham, 2008) . Coordination feedback (Wilson, Snapp-Childs, Coats, & Bingham, 2010) preserves that Information and we have recently shown that relative position supports transfer of learning between unimanual and bimanual performance of 90° (Snapp-Childs, Wilson, & Bingham, 2015). Here we ask whether that Information can support the production of other relative phases. We found large, asymmetric transfer of learning bimanual 90° to bimanual 60° and 120°, supported by Perceptual learning of relative position Information at 90°. For learning to transfer, the two tasks must overlap in some critical way; this is additional evidence that this overlap must be Informational. We discuss the results in the context of an ecological, task dynamical approach to understanding the nature of perception-action tasks.
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Learning a coordinated rhythmic movement with task-appropriate coordination feedback
Experimental Brain Research, 2010Co-Authors: Andrew D Wilson, Winona Snapp-childs, Rachel O. Coats, Geoffrey P. BinghamAbstract:A common perception–action learning task is to teach participants to produce a novel coordinated rhythmic movement, e.g. 90° mean relative phase. As a general rule, people cannot produce these novel movements stably without training. This is because they are extremely poor at discriminating the Perceptual Information required to coordinate and control the movement, which means people require additional (augmented) feedback to learn the novel task. Extant methods (e.g. visual metronomes, Lissajous figures) work, but all involve transforming the Perceptual Information about the task and thus altering the perception–action task dynamic being studied. We describe and test a new method for providing online augmented coordination feedback using a neutral colour cue. This does not alter the Perceptual Information or the overall task dynamic, and an experiment confirms that (a) feedback is required for learning a novel coordination and (b) the new feedback method provides the necessary assistance. This task-appropriate augmented feedback therefore allows us to study the process of learning while preserving the Perceptual Information that constitutes a key part of the task dynamic being studied. This method is inspired by and supports a fully perception–action approach to coordinated rhythmic movement.
Alessandro Saffiotti - One of the best experts on this subject based on the ideXlab platform.
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maintaining coherent Perceptual Information using anchoring
International Joint Conference on Artificial Intelligence, 2005Co-Authors: Amy Loutfi, Silvia Coradeschi, Alessandro SaffiottiAbstract:The purpose of this paper is to address the problem of maintaining coherent Perceptual Information in a mobile robotic system working over extended periods of time, interacting with a user and using multiple sensing modalities to gather Information about the environment and specific objects. We present a system which is able to use spatial and olfactory sensors to patrol a corridor and execute user requested tasks. To cope with Perceptual maintenance we present an extension of the anchoring framework capable of maintaining the correspondence between sensor data and the symbolic descriptions referring to objects. It is also capable of tracking and acquiring Information from observations derived from sensor-data as well as Information from a priori symbolic concepts. The general system is described and an experimental validation on a mobile robot is presented.
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IJCAI - Maintaining coherent Perceptual Information using anchoring
2005Co-Authors: Amy Loutfi, Silvia Coradeschi, Alessandro SaffiottiAbstract:The purpose of this paper is to address the problem of maintaining coherent Perceptual Information in a mobile robotic system working over extended periods of time, interacting with a user and using multiple sensing modalities to gather Information about the environment and specific objects. We present a system which is able to use spatial and olfactory sensors to patrol a corridor and execute user requested tasks. To cope with Perceptual maintenance we present an extension of the anchoring framework capable of maintaining the correspondence between sensor data and the symbolic descriptions referring to objects. It is also capable of tracking and acquiring Information from observations derived from sensor-data as well as Information from a priori symbolic concepts. The general system is described and an experimental validation on a mobile robot is presented.
Anna V Fisher - One of the best experts on this subject based on the ideXlab platform.
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processing of Perceptual Information is more robust than processing of conceptual Information in preschool age children evidence from costs of switching
Cognition, 2011Co-Authors: Anna V FisherAbstract:Is processing of conceptual Information as robust as processing of Perceptual Information early in development? Existing empirical evidence is insufficient to answer this question. To examine this issue, 3- to 5-year-old children were presented with a flexible categorization task, in which target items (e.g., an open red umbrella) shared category membership with one test item (e.g., a folded umbrella) and Perceptual characteristics with another test item (e.g., a red mushroom). Participants were instructed to either categorize stimuli by the same dimension (i.e., Perceptual similarity or category membership) in both phases of the task, or switch from categorizing by one dimension to categorizing by the other dimension. Results pointed to a strong asymmetry in switch costs: conceptual switch costs were higher than Perceptual switch costs. These results suggest that processing of Perceptual Information remains more robust than processing of conceptual Information at least until 5 years of age.
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Does Conceptual Information Take Precedence Over Perceptual Information Early in Development? Evidence From Perseveration Errors
2009Co-Authors: Anna V FisherAbstract:Does Conceptual Information Take Precedence Over Perceptual Information Early in Development? Evidence From Perseveration Errors Anna V. Fisher (fisher49@andrew.cmu.edu) Department of Psychology, Baker Hall 345-I 5000 Forbes Ave, Pittsburgh, PA 15213 USA Abstract Generalization is a fundamental cognitive process; however mechanisms of generalization early in development remain contested. According to one theoretical position, from very early in development conceptual Information takes precedence over Perceptual Information. According to the alternative position, effects of conceptual knowledge have a protracted developmental course. The goal of the present research was to examine directly whether 3- to 5-year-old children privilege conceptual Information over Perceptual Information. Participants were presented with triads of objects in which category membership conflicted with appearance similarity. Half of the children were first asked to sort pictures by category membership and then switch to sorting by similarity; the order of tasks was reversed for the other half of the children. A strong asymmetry in perseveration errors was observed across all three age groups: there was a marked decrease in accuracy when children were asked to switch form sorting by similarity to sorting by category membership, whereas the decrease was less pronounced when children were asked to switch from sorting by category membership to sorting by similarity (particularly for 4- and 5- year-old children who exhibited virtually no decrease in accuracy in the latter condition). Keywords: Categorization, Cognitive Cognitive Flexibility, Perseveration. Development; Introduction Generalization is a fundamental cognitive process because it allows us to acquire new knowledge by extending known to the unknown. Humans exhibit remarkable generalization abilities very early in development. For example, 3- and 4- month-old infants can learn to categorize artificial dot patterns (Bomba & Siqueland, 1983) as well as naturalistic stimuli (Quinn, Eimas, & Rosenkrantz, 1993); by 10 months of age infants are capable of performing simple generalizations about object properties, such as pattern of motion (Rakison, & Poulin-Dubois, 2002; Baldwin, Markman, & Melartin, 1993); and by 24 months of age children readily extend known labels to novel objects (Booth & Waxman, 2002; Jones & Smith, 1998; Smith, Jones, & Landau, 1996). However, mechanisms of generalization early in development remain contested. There is little disagreement in the literature that Perceptual factors influence both early and mature generalization (for review see Murphy, 2002). For instance, French, Mareschal, Mermillod, & Quinn (2004) demonstrated that 3- and 4-month-old infants form a representation of the category “cat” that excludes dogs, and a representation of the category “dog” that includes cats. The basis for this asymmetry was infants’ sensitivity to the distribution Information of Perceptual features (such as leg length, head width, ear separation, etc.) and the fact that feature distribution of the category “cat” is subsumed within the feature distribution of the category “dog”. Therefore, the asymmetry was reversed when infants were presented with a set of stimuli in which the inclusion relationship of the feature distributions was reversed (French, et. al., 2004). When children learn their first words, they extend new words to refer to correct objects or overextend new words to refer to items Perceptually similar to correct objects (Huttenlocher & Smiley, 1987). Importantly, Perceptual similarity effects are also well documented in mature generalization (Malt, 1994; Sloman, 1993; Osherson, Smith, Wilkie, Lopez, & Shafir, 1990; Nosofsky, 1984; Rips, Shoben, & Smith, 1973). There is also little disagreement that mature generalization is often influenced by conceptual factors, such as knowledge of the taxonomic hierarchies, expertise in a particular domain, or knowledge of an object’s function (Heit & Rubinstein, 1994; Proffitt, Coley, & Medin, 2000; Wisniewski, 1995). However, while conceptual effects in mature generalization are well documented, the developmental course of these effects remains unclear. One possibility is that early in development generalization processes are driven primarily by the low-level mechanisms of perception, attention, and memory, with conceptual factors emerging as an important influence on generalization later in development (McClelland, & Rogers, 2003; Rakison, 2003; Sloutsky, & Fisher, 2004; Sloutsky, 2003; Samuelson, & Smith, 2000; Smith, 2000). However, it has been argued that Perceptual factors alone are insufficient to explain early generalization, and conceptual factors (e.g., knowledge of the ontological status of the object) permeate learning from early infancy (Booth & Waxman, 2002; Gelman, 2003). Furthermore, it has been suggested that when Perceptual and conceptual Information are in conflict, conceptual Information “takes precedence” over Perceptual Information (Booth & Waxman, 2002; Gelman & Markman, 1986; Gelman, 2003). The goal of the present research was to address the question whether young children privilege conceptual Information over Perceptual Information using a task traditionally used to examine cognitive flexibility - a Dimension Change Card Sorting (DCCS) task, which is a simplified version of the Wisconsin Card Sort Test (Berg, 1948). In the DCCS task children are presented with a set
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Effects of Linguistic and Perceptual Information on Categorization in Young Children - eScholarship
2001Co-Authors: Vladimir M Sloutsky, Anna V FisherAbstract:Effects of linguistic and Perceptual Information on categorization in young children Vladimir M. Sloutsky (sloutsky.1@osu.edu) Center for Cognitive Science & School of Teaching & Learning Ohio State University 21 Page Hall, 1810 College Road Columbus, OH 43210, USA Anna V. Fisher (fisher.449@osu.edu) Center for Cognitive Science & School of Teaching & Learning Ohio State University 21 Page Hall, 1810 College Road Columbus, OH 43210, USA Abstract This paper examines the process of categorization in young children, and tests predictions derived from a model of young children’s similarity judgment. The model suggests that linguistic labels might have greater contribution to similarity judgment for younger children than do other attributes. It is argued that because categorization is based on similarity, the model predicting similarity judgment should also predict categorization. Predictions of the model were tested in the experiment where 4-6 year-olds were asked to perform a categorization task. Results of the experiment demonstrate that young children perform categorization in a similarity-based manner, and support both qualitative and quantitative predictions of the label-as- attribute model. Introduction The ability to group things together is an important component of human cognition: stimuli (i.e., objects, scenes, situations, or problems) rarely recur exactly, and, as a result, records of specific stimuli would be of little help. Therefore, the ability to form categories and store stimuli as members of these categories is a critical component of learning, memory, and thinking. Furthermore, it has been demonstrated that even infants are capable of forming categories (e.g., Balaban & Waxman, 1997; Quinn & Eimas, 1998; Mandler, 1997). It is less clear, however, how people form categories and include novel instances into a category. Several theories have emerged in an attempt to answer these questions (e.g., Lamberts & Shanks, 1997; Smith & Medin, 1984, for reviews). The general question of how people form categories and add new instances to these categories consists of three more specific questions: (1) How do people decide whether or not a novel entity is a member of an existing category? (2) How do people form a category when presented with a large number of positive and negative instances of the category? And (3) how do people decide whether or not two novel entities are members of the same novel category? While much theoretical and empirical work on categorization has focused on the first two questions (see Lamberts & Shanks, 1997; Smith & Medin, 1984, for reviews), the third question has remained largely under—researched. At the same time, answers to this question are important for understanding of the “first step” in the process of categorization — forming a new category and including some novel entities as its members, while excluding others. The current research attempts to examine the third question. As a first approximation, it appears plausible that, if no Information about the entities is available, the entities would be grouped together on the basis of their Perceptual similarity. Ifi in addition to Perceptual Information, there is also linguistic Information (e.g., “Look, here is an X”), then there are at least two possibilities for grouping. If the label X is familiar, then the object denoted as X could be included into all categories that include X as its member. However, if label X is novel, it seems likely that categorization should be performed on the basis of similarity. In this case, a model predicting similarity judgment should also predict categorization. One such model, the label- as—attribute model suggests that young children consider linguistic labels as attributes of compared entities (Sloutsky & Lo, 1999). The model predicts that both Perceptual and linguistic cues should contribute to comparison—based processes, such as similarity judgment. These predictions have been confirmed in a number of studies examining contribution of Perceptual and linguistic factors to similarity judgment (Sloutsky & Lo, 1999) and inductive inference (Sloutsky & Lo, 2000; Sloutsky, Lo, & Fisher, in press). It was found that young children aggregate Perceptual and linguistic cues when computing overall similarity among compared entities. We can predict, therefore, categorization should be a function of similarity computed over Perceptual and
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Effects of Linguistic and Perceptual Information on Categorization in Young Children
2001Co-Authors: Vladimir M Sloutsky, Anna V FisherAbstract:This paper examines the process of categorization in young children, and tests predictions derived from a model of young childrens similarity judgment. The model suggests that linguistic labels might have greater contribution to similarity judgment for younger children than do other attributes. It is argued that because categorization is based on similarity, the model predicting similarity judgment should also predict categorization. Predictions of the model were tested in the experiment where 4-6 year-olds were asked to perform a categorization task. Results of the experiment demonstrate that young children perform categorization in a similarity-based manner, and support both qualitative and quantitative predictions of the label-asattribute model.
Debin Zhao - One of the best experts on this subject based on the ideXlab platform.
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ICME - Reduced reference stereoscopic image quality assessment based on entropy of classified primitives
2017 IEEE International Conference on Multimedia and Expo (ICME), 2017Co-Authors: Feng Qi, Debin ZhaoAbstract:Stereoscopic vision is a complex system which receives and integrates Perceptual Information from both monocular and binocular cues. In this paper, a novel reduced-reference stereoscopic image quality assessment scheme is proposed, based on the visual Perceptual Information measured by entropy of classified primitives (EoCP) and mutual Information of classified primitives (MIoCP), named as DCprimary, sketch and texture primitives respectively, which is in accordance with the hierarchical progressive process of human visual perception. Specifically, EoCP of each-view image are calculated as monocular cue, and MIoCP between two-view images is derived as binocular cue. The Maximum (MAX) mechanism is applied to determine the Perceptual Information. The Perceptual Information differences between the original and distorted images are used to predict the stereoscopic image quality by support vector regression (SVR). Experimental results on LIVE phase II asymmetric database validate the proposed metric achieves significantly higher consistency with subjective ratings and outperforms state-of-the-art stereoscopic image quality assessment methods.
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reduced reference stereoscopic image quality assessment based on binocular Perceptual Information
IEEE Transactions on Multimedia, 2015Co-Authors: Feng Qi, Debin ZhaoAbstract:In this paper, we propose a novel reduced reference stereoscopic image quality assessment (RR-SIQA) metric by using binocular Perceptual Information (BPI). BPI is represented by the distribution statistics of visual primitives in left and right views’ images, which are extracted by sparse coding and representation . Specifically, entropy of the left view’s image and entropy of the right view’s image are used to represent monocular cue. Their mutual Information is used to represent binocular cue. Constructively, we represent BPI as three numerical indicators . The difference of the original and distorted images’ BPIs is taken as Perceptual loss vector. The Perceptual loss vector is used to compute the quality score for a stereoscopic image by a prediction function which is trained using support vector regression (SVR). Experimental results show that the proposed metric achieves significantly higher prediction accuracy than the state-of-the-art reduced reference SIQA methods and better than several state-of-the-art full reference SIQA methods on the LIVE phase II asymmetric databases.
