Abstract. We present a clustering approach for video summarization and browsing based on the Growing Cell Structures (GCS) neural algorithms and MPEG-7 video descriptors. Each I frame is represented as a feature vector of MPEG-7 descriptors. These vectors are clustered using GCS to select one or more keyframes for each shot. The extracted keyframes are then grouped together by TreeGCS to form a hierarchical view of the video for efficient browsing. We evaluate the effectiveness of different combinations of MPEG-7 descriptors and also compare them with the performance of color histograms.