The Experts below are selected from a list of 167052 Experts worldwide ranked by ideXlab platform
Francisco Sandoval - One of the best experts on this subject based on the ideXlab platform.
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Fast gesture recognition based on a two-level representation
Pattern Recognition Letters, 2009Co-Authors: J.p. Bandera, Rebeca Marfil, Antonio Bandera, J. A. Rodríguez, Luis Molina-tanco, Francisco SandovalAbstract:Towards developing an interface for human-robot interaction, this paper proposes a two-level approach to recognise gestures which are composed of trajectories followed by different body parts. In a first level, individual trajectories are described by a set of key-points. These points are chosen as the corners of the curvature function associated to the trajectory, which will be estimated using and adaptive, non-iterative scheme. This adaptive representation allows removing noise while preserving detail in curvature at different scales. In a second level, gestures are characterised through global properties of the trajectories that compose them. Gesture recognition is performed using a Confidence Value that integrates both levels. Experimental results show that the performance of the proposed method is high in terms of computational cost and memory consumption, and gesture recognition ability.
Rajiv Gupta - One of the best experts on this subject based on the ideXlab platform.
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PLDI - Pruning dynamic slices with Confidence
Proceedings of the 2006 ACM SIGPLAN conference on Programming language design and implementation - PLDI '06, 2006Co-Authors: Xiangyu Zhang, Neelam Gupta, Rajiv GuptaAbstract:Given an incorrect Value produced during a failed program run (e.g., a wrong output Value or a Value that causes the program to crash), the backward dynamic slice of the Value very frequently captures the faulty code responsible for producing the incorrect Value. Although the dynamic slice often contains only a small percentage of the statements executed during the failed program run, the dynamic slice can still be large and thus considerable effort may be required by the programmer to locate the faulty code.In this paper we develop a strategy for pruning the dynamic slice to identify a subset of statements in the dynamic slice that are likely responsible for producing the incorrect Value. We observe that some of the statements used in computing the incorrect Value may also have been involved in computing correct Values (e.g., a Value produced by a statement in the dynamic slice of the incorrect Value may also have been used in computing a correct output Value prior to the incorrect Value). For each such executed statement in the dynamic slice, using the Value profiles of the executed statements, we compute a Confidence Value ranging from 0 to 1 - a higher Confidence Value corresponds to greater likelihood that the execution of the statement produced a correct Value. Given a failed run involving execution of a single error, we demonstrate that the pruning of a dynamic slice by excluding only the statements with the Confidence Value of 1 is highly effective in reducing the size of the dynamic slice while retaining the faulty code in the slice. Our experiments show that the number of distinct statements in a pruned dynamic slice are 1.79 to 190.57 times less than the full dynamic slice. Confidence Values also prioritize the statements in the dynamic slice according to the likelihood of them being faulty. We show that examining the statements in the order of increasing Confidence Values is an effective strategy for reducing the effort of fault location.
Sébastien Destercke - One of the best experts on this subject based on the ideXlab platform.
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Evaluating trust from past assessments with imprecise probabilities: comparing two approaches
Lecture Notes in Computer Science, 2010Co-Authors: Sébastien DesterckeAbstract:In this paper, we consider a trust system where the trust in an agent is evaluated from past assessments made by other agents. We consider that trust is evaluated by Values given on a finite scale. To model the agent trustworthiness, we propose to build imprecise probabilistic models from these assessments. More precisely, we propose to derive probability intervals (i.e., bounds on singletons) using two different approaches: Goodman’s multinomial Confidence regions and the imprecise Dirichlet model (IDM). We then use these models for two purposes: (1) evaluating the chances that a future assessments will take particular Values, and (2) computing an interval summarizing the agent trustworthiness, eventually fuzzyfying this interval by letting the Confidence Value vary over the unit interval. We also give some elements of comparison between the two approaches.
D. Brzakovic - One of the best experts on this subject based on the ideXlab platform.
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3-D scene reconstruction from noisy image sequences using data fusion
Control Engineering Practice, 1994Co-Authors: L. Hong, D. BrzakovicAbstract:Abstract The system reconstructs 3-D scenes from sequences of noisy binocular images. First, the system establishes possible matches between the feature pixels in the first image pair and assigns a Confidence Value to a possible match. Each possible match is associated with a 3-D volume. The possible matches are used to predict projections of associated 3-D volumes onto the remaining image pairs. The new matches are used to update Confidence Values using a Kalman filtering related fusion algorithm. Finally, matches pixels with high Confidence Values are used to reconstruct a 3-D scene.
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ICCV - An approach to 3D scene reconstruction from noisy binocular image sequences using information fusion
[1990] Proceedings Third International Conference on Computer Vision, 1Co-Authors: L. Hong, D. BrzakovicAbstract:The vision system described reconstructs 3D scenes from sequences of noisy binocular images. First, the system establishes all possible matches between the feature pixels in the first binocular image pair and assigns a Confidence Value to a possible match. Each possible match is associated with a 3D volume. The possible matches are used to predict projections of associated 3D volumes onto the remaining binocular image pairs. These projections are utilized to limit searches for possible matches. The matches are used to update Confidence Values using an optimal fusion algorithm. Finally, matched pixels with high Confidence Values are used to reconstruct a 3D scene. >
J.p. Bandera - One of the best experts on this subject based on the ideXlab platform.
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Fast gesture recognition based on a two-level representation
Pattern Recognition Letters, 2009Co-Authors: J.p. Bandera, Rebeca Marfil, Antonio Bandera, J. A. Rodríguez, Luis Molina-tanco, Francisco SandovalAbstract:Towards developing an interface for human-robot interaction, this paper proposes a two-level approach to recognise gestures which are composed of trajectories followed by different body parts. In a first level, individual trajectories are described by a set of key-points. These points are chosen as the corners of the curvature function associated to the trajectory, which will be estimated using and adaptive, non-iterative scheme. This adaptive representation allows removing noise while preserving detail in curvature at different scales. In a second level, gestures are characterised through global properties of the trajectories that compose them. Gesture recognition is performed using a Confidence Value that integrates both levels. Experimental results show that the performance of the proposed method is high in terms of computational cost and memory consumption, and gesture recognition ability.