Cognitive vision systems : sampling the spectrum of approaches

Introductory Remarks.- Introductory Remarks.- I Foundations of Cognitive Vision Systems.- The Space of Cognitive Vision.- Cognitive Vision Needs Attention to Link Sensing with Recognition.- Organization of Architectures for Cognitive Vision Systems.- Cognitive Vision Systems: From Ideas to Specifications.- II Recognition and Categorization.- A System for Object Class Detection.- Greedy Kernel Principal Component Analysis.- Many-to-Many Feature Matching in Object Recognition.- Integrating Video Information over Time. Example: Face Recognition from Video.- Interleaving Object Categorization and Segmentation.- III Learning and Adaptation.- Learning an Analysis Strategy for Knowledge-Based Exploration of Scenes.- IV Representation and Inference.- Things That See: Context-Aware Multi-modal Interaction.- Hierarchies Relating Topology and Geometry.- Cognitive Vision: Integrating Symbolic Qualitative Representations with Computer Vision.- On Scene Interpretation with Description Logics.- V Control and Systems Integration.- A Framework for Cognitive Vision Systems or Identifying Obstacles to Integration.- Visual Capabilities in an Interactive Autonomous Robot.- VI Conclusions.- On Sampling the Spectrum of Approaches Toward Cognitive Vision Systems.