Combining Structural Descriptions and Image-based Representations for Image, Object, and Scene Recognition

Object and scene learning and recognition is a major issue in computer vision, in robotics and in cognitive sciences. This paper presents the principles and results of an approach which extracts structured view-based representations for multi-purpose recognition. The structures are hierarchical and distributed and provide for generalization and categorization. A tracking process enables to bind views over time and to link consecutive views. Scenes can also be recognized using objects as components. Illustrative results are presented.