Motion-based video object indexing using multiresolution analysis

In this paper, we describe an efficient video indexing scheme based on motion behavior of video objects for fast content-based browsing and retrieval in a video database. The proposed novel method constructs a dictionary of prototype objects. The first step in our approach extracts moving objects by analyzing layered images constructed from the coarse data in a 3D wavelet decomposition of the video sequence. These images capture motion information only. Moving objects are modeled as collections of interconnected rigid polygonal shapes in the motion sequences that we derive from the wavelet representation. The motion signatures of the object are computed from the rotational and translational motions associated to the elemental polygons that form the objects. These signatures are finally stored as potential query terms.