3D shape inferencing and modeling for video retrieval

We present a geometry-based indexing approach for the retrieval of video da tabases. It consists of two modules: 3D object shape inferencing from video data and geometric modeling from the reconstructed shape structure. A moti on-based segmentation algorithm employing feature block tracking and princi pal component split is used for multi-moving-object motion classification a nd segmentation. After segmentation, feature blocks from each individual ob ject are used to reconstruct its motion and structure through a factorizati on method. The estimated shape structure and motion parameters are used to generate the implicit polynomial model for the object. The video data is re trieved using the geometric structure of objects and their spatial relation ship. We generalize the 2D string to 3D to compactly encode the spatial rel ationship of objects. (C) 2000 Academic Press.