Surveillance system with megapixel scalable transcoder This paper presents a video surveillance system that displays megapixel streams effectively, while transmitting and processing the streams efficiently with limited resources such as bandwidth, computing power and display resolution. The proposed system stores highresolution and highquality video data and associated object metadata, which includes ROI (RegionofInterest) information. To satisfy such resource constraints and display important parts in detail without missing the overall scene context, the stored images are efficiently transcoded in the compresseddomain based on the ROI information, display resolution and available bandwidth. Simulation results confirm the effectiveness of the proposed system in terms of objective measures and subjective evaluation.

An Efficient Coding Scheme for Surveillance Videos Captured by Stationary Cameras In this paper, a new scheme is presented to improve the coding efficiency of sequences captured by stationary cameras (or namely, static cameras) for video surveillance applications. We introduce two novel kinds of frames (namely background frame and difference frame) for input frames to represent the foregroundbackground without object detection, tracking or segmentation. The background frame is built using a background modeling procedure and periodically updated while encoding. The difference frame is calculated using the input frame and the background frame. A sequence structure is proposed to generate high quality background frames and efficiently code difference frames without delay, and then surveillance videos can be easily compressed by encoding the background frames and difference frames in a traditional manner. In practice, the H.264AVC encoder JM 16.0 is employed as a buildin coding module to encode those frames. Experimental results on eight indoor and outdoor surveillance videos show that the proposed scheme achieves 0.12 dB1.53 dB gain in PSNR over the JM 16.0 anchor specially configured for surveillance videos.