Image retrieval and classification using affine invariant B-spline representation and neural networks

In this paper, a system for content-based image retrieval from video databases is introduced, using B-splines for affine invariant object representation. A small number of "keyframes" is extracted from each video sequence, which provide sufficient information about the video content. Color and motion segmentation and tracking is then employed for automatic extraction of video objects. A B-spline representation of the object contours is then obtained, which possesses important properties, such as smoothness, continuity and invariance under affine transformation. A neural network approach is used for supervised classification of video objects into prototype object classes. Finally, higher level classes can be constructed combining primary classes, providing the ability to obtain a high level of abstraction in the representation of each video sequence.