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Carles Fernandez, Pau Baiget, Xavier Roca, & Jordi Gonzalez. (2008). Interpretation of Complex Situations in a Semantic-based Surveillance Framework. Signal Processing: Image Communication, Special Issue on Semantic Analysis for Interactive Multimedia Services, 554–569.
Abstract: The integration of cognitive capabilities in computer vision systems requires both to enable high semantic expressiveness and to deal with high computational costs as large amounts of data are involved in the analysis. This contribution describes a cognitive vision system conceived to automatically provide high-level interpretations of complex real-time situations in outdoor and indoor scenarios, and to eventually maintain communication with casual end users in multiple languages. The main contributions are: (i) the design of an integrative multilevel architecture for cognitive surveillance purposes; (ii) the proposal of a coherent taxonomy of knowledge to guide the process of interpretation, which leads to the conception of a situation-based ontology; (iii) the use of situational analysis for content detection and a progressive interpretation of semantically rich scenes, by managing incomplete or uncertain knowledge, and (iv) the use of such an ontological background to enable multilingual capabilities and advanced end-user interfaces. Experimental results are provided to show the feasibility of the proposed approach.
Keywords: Cognitive vision system; Situation analysis; Applied ontologies
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Mikhail Mozerov, Ariel Amato, Xavier Roca, & Jordi Gonzalez. (2008). Trajectory Occlusion Handling with Multiple View Distance Minimisation Clustering. Optical Engineering, vol. 47(04)04702, DOI:10.11781.2909665.
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Ignasi Rius, Jordi Gonzalez, Mikhail Mozerov, & Xavier Roca. (2008). Automatic Learning of 3D Pose Variability in Walking Performances for Gait Analysis. International Journal for Computational Vision and Biomechanics, 33–43.
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Carles Fernandez, Xavier Roca, & Jordi Gonzalez. (2008). Providing Automatic Multilingual Text Generation to Artificial Cognitive Systems.
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Josep Llados, Enric Marti, & Juan J.Villanueva. (2001). Symbol recognition by error-tolerant subgraph matching between region adjacency graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(10), 1137–1143.
Abstract: The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.
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