A task-oriented vision system

Yang Xiao, Kevin Irick, John Morgan Sampson, Vijaykrishnan Narayanan, Chuanjun Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently, biologically inspired vision systems have been the focus of intense research effort to emulate the high energy-efficiency, performance and robustness of mammalian vision systems. However, previous vision accelerators have only focused on speeding up computationally intense portions of the system without exploiting effects seen in the human brain that demonstrate the task influence in the vision mechanism. In this paper, we propose a task-oriented two-level vision system which is composed of Saliency and SURF. To the best of our knowledge, our design is the first embedded system that utilizes task influence in the computation of visual attention and recognition. As a result, we show that the new system can achieve at most 12.75% accuracy improvement while saving 25% computation work.

Original languageEnglish (US)
Title of host publicationGLSVLSI 2014 - Proceedings of the 2014 Great Lakes Symposium on VLSI
PublisherAssociation for Computing Machinery
Pages181-186
Number of pages6
ISBN (Print)9781450328166
DOIs
StatePublished - Jan 1 2014
Event24th Great Lakes Symposium on VLSI, GLSVLSI 2014 - Houston, TX, United States
Duration: May 21 2014May 23 2014

Publication series

NameProceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI

Other

Other24th Great Lakes Symposium on VLSI, GLSVLSI 2014
CountryUnited States
CityHouston, TX
Period5/21/145/23/14

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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