tailieunhanh - Báo cáo hóa học: " Research Article Feature-Based Image Comparison for Semantic Neighbor Selection in Resource-Constrained Visual Sensor Networks"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Feature-Based Image Comparison for Semantic Neighbor Selection in Resource-Constrained Visual Sensor Networks | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2010 Article ID 469563 11 pages doi 2010 469563 Research Article Feature-Based Image Comparison for Semantic Neighbor Selection in Resource-Constrained Visual Sensor Networks Yang Bai and Hairong Qi Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville TN 37996 USA Correspondence should be addressed to Yang Bai ybai2@ Received 28 December 2009 Revised 22 May 2010 Accepted 20 September 2010 Academic Editor Li-Qun Xu Copyright 2010 Y. Bai and H. Qi. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Visual Sensor Networks VSNs formed by large number of low-cost small-size visual sensor nodes represent a new trend in surveillance and monitoring practices. Sensor collaboration is essential to VSNs and normally performed among sensors having similar measurements. The directional sensing characteristics of imagers and the presence of visual occlusion present unique challenges to neighborhood formation as geographically-close neighbors might not monitor similar scenes. In this paper we propose the concept of forming semantic neighbors where collaboration is only performed among geographically-close nodes that capture similar images thus requiring image comparison as a necessary step. To avoid large amount of data transfer we propose feature-based image comparison as features provide more compact representation of the image. The paper studies several representative feature detectors and descriptors in order to identify a suitable feature-based image comparison system for the resource-constrained VSN. We consider two sets of metrics from both the resource consumption and accuracy perspectives to evaluate various combinations of feature detectors and descriptors. Based on .

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