Surveillance centric coding

PhDThe research work presented in this thesis focuses on the development of techniques specific to surveillance videos for efficient video compression with higher processing speed. The Scalable Video Coding (SVC) techniques are explored to achieve higher compression efficiency. The framework of SVC is modified to support Surveillance Centric Coding (SCC). Motion estimation techniques specific to surveillance videos are proposed in order to speed up the compression process of the SCC. The main contributions of the research work presented in this thesis are divided into two groups (i) Efficient Compression and (ii) Efficient Motion Estimation. The paradigm of Surveillance Centric Coding (SCC) is introduced, in which coding aims to achieve bit-rate optimisation and adaptation of surveillance videos for storing and transmission purposes. In the proposed approach the SCC encoder communicates with the Video Content Analysis (VCA) module that detects events of interest in video captured by the CCTV. Bit-rate optimisation and adaptation are achieved by exploiting the scalability properties of the employed codec. Time segments containing events relevant to surveillance application are encoded using high spatiotemporal resolution and quality while the irrelevant portions from the surveillance standpoint are encoded at low spatio-temporal resolution and / or quality. Thanks to the scalability of the resulting compressed bit-stream, additional bit-rate adaptation is possible; for instance for the transmission purposes. Experimental evaluation showed that significant reduction in bit-rate can be achieved by the proposed approach without loss of information relevant to surveillance applications. In addition to more optimal compression strategy, novel approaches to performing efficient motion estimation specific to surveillance videos are proposed and implemented with experimental results. A real-time background subtractor is used to detect the presence of any motion activity in the sequence. Different approaches for selective motion estimation, GOP based, Frame based and Block based, are implemented. In the former, motion estimation is performed for the whole group of pictures (GOP) only when a moving object is detected for any frame of the GOP. iii While for the Frame based approach; each frame is tested for the motion activity and consequently for selective motion estimation. The selective motion estimation approach is further explored at a lower level as Block based selective motion estimation. Experimental evaluation showed that significant reduction in computational complexity can be achieved by applying the proposed strategy. In addition to selective motion estimation, a tracker based motion estimation and fast full search using multiple reference frames has been proposed for the surveillance videos. Extensive testing on different surveillance videos shows benefits of application of proposed approaches to achieve the goals of the SCC

Energy-efficient bandwidth allocation for multiuser scalable video streaming over WLAN

We consider the problem of packet scheduling for the transmission of multiple video streams over a wireless local area network (WLAN). A cross-layer optimization framework is proposed to minimize the wireless transceiver energy consumption while meeting the user required visual quality constraints. The framework relies on the IEEE 802.11 standard and on the embedded bitstream structure of the scalable video coding scheme. It integrates an application-level video quality metric as QoS constraint (instead of a communication layer quality metric) with energy consumption optimization through link layer scaling and sleeping. Both energy minimization and min-max energy optimization strategies are discussed. Simulation results demonstrate significant energy gains compared to the state-of-the-art approaches

Forward Error Correction applied to JPEG-XS codestreams

JPEG-XS offers low complexity image compression for applications with constrained but reasonable bit-rate, and low latency. Our paper explores the deployment of JPEG-XS on lossy packet networks. To preserve low latency, Forward Error Correction (FEC) is envisioned as the protection mechanism of interest. Despite the JPEG-XS codestream is not scalable in essence, we observe that the loss of a codestream fraction impacts the decoded image quality differently, depending on whether this codestream fraction corresponds to codestream headers, to coefficients significance information, or to low/high frequency data, respectively. Hence, we propose a rate-distortion optimal unequal error protection scheme that adapts the redundancy level of Reed-Solomon codes according to the rate of channel losses and the type of information protected by the code. Our experiments demonstrate that, at 5% loss rates, it reduces the Mean Squared Error by up to 92% and 65%, compared to a transmission without and with optimal but equal protection, respectively