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Chapter and Conference Paper
Automatic Learning of Conceptual Knowledge in Image Sequences for Human Behavior Interpretation
This work describes an approach for the interpretation and explanation of human behavior in image sequences, within the context of a Cognitive Vision System. The information source is the geometrical data obtaine...
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Chapter and Conference Paper
Natural Language Descriptions of Human Behavior from Video Sequences
This contribution addresses the generation of textual descriptions in several natural languages for evaluation of human behavior in video sequences. The problem is tackled by converting geometrical information...
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Chapter and Conference Paper
A 3D Dynamic Model of Human Actions for Probabilistic Image Tracking
In this paper we present a method suitable to be used for human tracking as a temporal prior in a particle filtering framework such as CONDENSATION [5]. This method is for predicting feasible human postures given...
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Chapter and Conference Paper
Probabilistic Image-Based Tracking: Improving Particle Filtering
Condensation is a widely-used tracking algorithm based on particle filters. Although some results have been achieved, it has several unpleasant behaviours. In this paper, we highlight the...
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Chapter and Conference Paper
Multiple Model Approach to Deformable Shape Tracking
This paper describes a new proposal for tracking deformable objects in video sequences using multiple shape models of heterogeneous dimensionality. This models are generated unsupervisedly from a training sequ...