Compression

storage

and transmission of local feature descriptors have shown remarkable importance in a wide range of image and video applications. In this paper

a hybrid frame work of conventional image/video compression and compact feature representation is developed to make the multimedia smarter for retrieval/analysis driven applications. The multiple-reference prediction technique is introduced to remove the redundancy from both spatial-temporal domain and texture feature by efficiently leveraging the information in video coding. This process is done to achieve compact

discriminative

and efficient representation of feature descriptors. Furthermore

the rate-accuracy optimization technique

which targets to optimize the performance in matching/retrieval based applications

is introduced. Based on the extensive simulations on different test databases

the bitrate of visual features is significantly reduced according to the proposed scheme to wards 150:1 compression ratio

while maintaining a state-of-the-art matching/retrieval performance. The proposed system has demonstrated its efficiency and effectiveness toward novel multimedia compression framework for various applications in smart devices.