Coding and Analysis Subsystems of Distributed Video Sensors
PI: Prof. Shao-Yi Chien Co-PI: Dr. Chia-han Lee
Intel Champions: Dr. V Srinivasa Somayazulu & Dr. Y. K. Chen
An application of M2M networks we consider has clusters of video sensors/cameras capturing images (with potentially overlapping fields of view) and communicating the video data to aggregation points which fuse and analyze the data from different video sensors. The key requirements on the sensors are to minimize the energy consumption and complexity while maximizing the quality of video gathered at the aggregation points.
Distributed video coding (DVC) has been considered as an elegant solution to this problem for the multiple-sensor case as well as for a single-sensor case respectively. In this project, we plan to extend the design space from algorithm design for point-to-point data transmission to system/hardware/algorithm design for content analysis and transmission in a sensor-aggregation-cloud architecture.
The target of this project is to develop coding and analysis subsystems of distributed video sensors that employ distributed video coding techniques to scale with the energy consumption/complexity of the sensor and aggregation nodes. An improvement of 3x–4x power efficiency is expected in this project for different cases, including cases on ASIC based platform or processor based platform.
Members
Publications
S. Ou et al., "Video sensor node with distributed video summary for Internet-of-Things applications", in 2015 IEEE International Conference on Consumer Electronics - Taiwan, pp. 304-305.
S. Chien et al., "Distributed computing in IoT: System-on-a-chip for smart cameras as an example", in The 20th Asia and South Pacific Design Automation Conference, 2015, pp. 130-135.
S. Ou et al., "Communication-efficient multi-view keyframe extraction in distributed video sensors", in 2014 IEEE Visual Communications and Image Processing Conference, pp. 13-16.
C. Lee, Z. Syu, "Handover Analysis of Macro-Assisted Small Cell Networks", in 2014 IEEE International Conference on Internet of Things (iThings), and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom), pp. 604-609.
C. Liu, C. Lee, "MISO information and power transfer with finite-rate feedback under fading channel", in 2014 IEEE International Conference on Communications (ICC), pp. 3794-3799.
H. Wu et al., "Error resilience for key frames in distributed video coding with rate-distortion optimized mode decision", in 2014 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 1118-1121.
S. Ou et al., "Low complexity on-line video summarization with Gaussian mixture model based clustering", in 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1260-1264.
Y. Lan et al., "Active precoder identification for inter-cell interference mitigation in heterogeneous networks", in 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), pp. 1222-1226.
C. Wu et al., "Practical Physical Layer Security Schemes for MIMO-OFDM Systems Using Precoding Matrix Indices", IEEE Journal on Selected Areas in Communications, vol. 31, no. 9, 2013, pp. 1687-1700.
Y. Wang et al., "Low-complexity feedback-channel-free distributed video coding with enhanced classifier", in 2013 IEEE International Symposium on Circuits and Systems (ISCAS), pp. 257-260.
National Taiwan University
