Optimal sensor selection for video-based target tracking in a wireless sensor network

The use of wireless sensor networks for target tracking is an active area of research. Imaging sensors that obtain video-rate images of a scene can have a significant impact in such networks, as they can measure vital information on the identity, position, and velocity of moving targets. Since wireless networks must operate under stringent energy constraints, it is important to identify the optimal set of imagers to be used in a tracking scenario such that the network lifetime is maximized. We formulate this problem as one of maximizing the information utility gained from a set of sensors subject to a constraint on the average energy consumption in the network. We use an unscented Kalman filter framework to solve the tracking and data fusion problem with multiple imaging sensors in a computationally efficient manner, and use a lookahead algorithm to optimize the sensor selection based on the predicted trajectory of the target. Simulation results show the effectiveness of this method of sensor selection. 1

Rate-Distortion Optimized Video Summary Generation and Transmission Over Packet Lossy Networks

The goal of video summarization is to select key frames from a video sequence in order to generate an optimal summary that can accommodate constraints on viewing time, storage, or bandwidth. While video summary generation without transmission considerations has been studied extensively, the problem of rate-distortion optimized summary generation and transmission in a packet-lossy network has gained little attention. We consider the transmission of summarized video over a packet-lossy network such as the Internet. We depart from traditional rate control methods by not sacrificing the image quality of each transmitted frame but instead focusing on the frames that can be dropped without seriously affecting the quality of the video sequence. We take into account the packet loss probability, and use the end-to-end distortion to optimize the video quality given constraints on the temporal rate of the summary. Different network scenarios such as when a feedback channel is not available, and when a feedback channel is available with the possibility of retransmission, are considered. In each case, we assume a strict end-to-end delay constraint such that the summarized video can be viewed in real-time. We show simulation results for each case, and also discuss the case when the feedback delay may not be constant