Image quilting heuristic compressed sensing video privacy protection coding for abnormal behavior detection in private scenes

For video intelligence applications in private scenes such as home environments, traditional image processing methods are usually based on clear raw data and are prone to privacy leakage. Therefore, our team proposed multilayer compressed sensing (MCS) encoding to reduce image quality for visual privacy protection (VPP). However, the way in which MCS coding is implemented leads to unavoidable information loss. On this basis, inspired by the image quilting (IQ) algorithm, an image quilting heuristic MCS (IQ-MCS) coding method is proposed in this paper to improve the problem of faster information loss in the MCS coding process, which means that a similar privacy protection effect is achieved at lower coding layers, thus obtaining better application performance. To evaluate the level of VPP, a VPP evaluation algorithm is proposed that is more in line with subjective assessment. Finally, a correlation model between the VPP level and the performance of smart applications is established to balance the relationships between them, taking the detection of abnormal human behavior in private scenes as an example. The model can also provide a reference for the evaluation of other privacy protection methods.