Covert Video Classification by Codebook Growing Pattern

Liang Du, Haitao Lang, Ying-Li Tian, Chiu C. Tan, Jie Wu, Haibin Ling; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016, pp. 11-18

Recent advances in visual data acquisition and Internet technologies make it convenient and popular to collect and share videos. These activities, however, also raise the issue of privacy invasion. One potential privacy threaten is the unauthorized capturing and/or sharing of covert videos, which are recorded without the awareness of the subject(s) in the video. In this paper, we propose a novel descriptor, codebook growing pattern (CGP), which is derived from latent Dirichlet allocation (LDA) over optical flows. To evaluate the proposed approach, we collected a large covert video dataset, the first such dataset to our knowledge, and tested the proposed method on the dataset. The results show clearly the effectiveness of the proposed approach in comparison with other state-of-the-art video classification algorithms.