Extraction of visual descriptor is a crucial problem for state- of-the-art visual information analysis. In this paper, we present a knowledge-based approach for detection of visual objects in video sequences. The propose approach models objects through their visual descriptors defined in MPEG7. It first extracts moving regions using an efficient active contours technique. It then computes visual descriptions of the moving regions including color features, shape features which are invariant to affine transformations, as well as motion features. The extracted features are matched to a-priori knowledge about the objects’ descriptions,using appropriately defined matching functions. Results are presented which illustrate the theoretical developments