Monitoring Activities from Multiple Video Streams: Establishing a Common Coordinate Frame
IEEE Transactions on Pattern Analysis and Machine Intelligence
Event Detection and Analysis from Video Streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
Understanding Smart Sensors, Second Edition
Understanding Smart Sensors, Second Edition
Vision Chips
Using Adaptive Tracking to Classify and Monitor Activities in a Site
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
MPI-Video Infrastructure for Dynamic Environments
ICMCS '98 Proceedings of the IEEE International Conference on Multimedia Computing and Systems
IEEE Transactions on Circuits and Systems for Video Technology
Parallel processing for image and video processing: Issues and challenges
Parallel Computing
Hi-index | 0.00 |
Large-scale image sensing over the extended area with multiple image sensors is considered very effective for collecting and analyzing global information, which is hard to be achieved by a single or small number of image sensors. However, if they share the network resources simultaneously, how to transfer and process vast amount of data caused by numerous sensors is one of the critical issues to implement a practical system. In this paper, we present a new approach to large-scale image sensing system using random accessible smart image sensors to reduce the data volume at image acquisition level. By the pixel-level data management throughout the whole processing, both network and system resources can be saved while preserving the main region of the scenes. Based on the simulation results regarding spatial/temporal resolution schemes, an experimental system using multiple sensors is implemented and the basic results are provided.