An efficient coding framework for compact descriptors extracted from video sequence

Abstract

Towards effective and efficient image matching or retrieval tasks, the emerging MPEG standard, named Compact Descriptors for Visual Search (CDVS), has fulfilled compact descriptors for still images, consisting of compressed local and global descriptor. Nevertheless, the frame-level coding of CDVS descriptors from a video sequence does not address the inter-frame redundancy issue, which may consume considerable bandwidth and storage resources. In this work, we propose an efficient coding framework of CDVS descriptors to generate compact descriptors for video sequences. For local descriptors, we propose a multiple reference predictive technique to exploit the temporal correlation of local descriptors and location coordinates over a sequence of frames. To further improve the prediction performance, keypoint tracking is applied to identify temporally repeated keypoints. For global descriptors, a propagation coding way is employed to compress the global descriptors of adjacent frames. The empirical evaluation has shown that the proposed coding approach has yielded a low bit rate of less than 40kbps on average, while maintaining comparable matching and retrieval performance. Compared to the sequence of original frame-level CDVS descriptors, the proposed approach has achieved over 25× bit rate reduction.