Experimental results indicate that our detection method achieves high detection recall, precision, and F1-score for surveillance videos of both high and low resolutions with various scenes. Spatial and temporal consistency of a moving object and Kalman filtering are applied to segment connected/merged motion regions, remove noise and background motions, and refine trajectories and shapes of detected moving objects. The partition pattern and the number of coding bits of each detection block used in prior art are also used to help detect motion regions. It adopts a novel approach that exploits inter-prediction reference relationships among coding blocks to detect motion regions. In this article, we propose the first motion detection method on encrypted and HEVC-compressed videos. The existing scheme, designed to detect motion on encrypted and H.264-compressed surveillance videos, does not work well on more advanced video compression schemes such as HEVC. Privacy-preserving video surveillance allows motion detection while protecting privacy. Cloud-based video surveillance requires motion detection, which may reveal the privacy of people in a surveillance video. The risk of privacy leakage has become a major concern for cloud users. ![]() In the cloud era, a large amount of data is uploaded to and processed by public clouds. Our scheme is applicable to other audio compression standards based on similar technologies. Our FLAC decoding scheme enables Single-Instruction Multiple-Data (SIMD): multiple (e.g., 256) plaintexts are packed and encrypted into a single ciphertext, and decoding one encrypted frame corresponds to decoding multiple plaintext frames. The summation of each control value's candidate results multiplied by its matching bit is equivalent to selecting the results of the matched control value. Our scheme regularizes dynamic controls in FLAC decoding with static controls by calculating an encrypted matching bit for each possible value of a control variable and producing candidate results as if it were a match. FLAC decoding relies heavily on dynamic controls that HE does not support due to unknown values of control variables after encryp-tion. FLAC applies linear prediction to predict the current sample and Golomb coding to encode residuals. ![]() In this paper, we propose a novel scheme to enable FLAC (Free Lossless Audio Codec) decompression in the HE domain. Homomorphic Encryption (HE) allows processing cipher-text data, but it is a challenge to enable complex methods such as multimedia decompression in the HE domain.
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