Confidence-driven architecture for real-time vision processing and its application to efficient vision-based human motion sensing

Hiromasa Yoshimoto, Naoto Date, Daisaku Arita, Rin Ichiro Taniguchi

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

5 Citations (Scopus)

Abstract

In this paper, we discuss a real-time vision architecture which provides a mechanism of controlling trade-off between the accuracy and the latency of vision systems. In vision systems, to acquire accurate information from input-images, the huge amount of computation power is usually required. On the other hand, to realize real-time processing, we must reduce the latency. Therefore, under given hardware resources, we must make difficult trade-off between the accuracy and the latency so that the quality of the system's output keeps appropriate. To solve the problem, we propose confidence-driven scheme, which enables us to control the trade-off dynamically and easily without rebuilding vision systems. In the confidence-driven architecture, the trade-off can be controlled by specifying a generalized parameter called confidence, which relatively indicates how accurate the analysis should be. Here, we present the concept of confidence-driven architecture, and then, we show a shared memory which uses confidence-driven scheme. Using confidence-driven memory, we can use imprecise computation model to reduce the latency without a large decrease of accuracy.

Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
EditorsJ. Kittler, M. Petrou, M. Nixon
Pages736-740
Number of pages5
DOIs
Publication statusPublished - 2004
EventProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004 - Cambridge, United Kingdom
Duration: Aug 23 2004Aug 26 2004

Publication series

NameProceedings - International Conference on Pattern Recognition
Volume1
ISSN (Print)1051-4651

Other

OtherProceedings of the 17th International Conference on Pattern Recognition, ICPR 2004
CountryUnited Kingdom
CityCambridge
Period8/23/048/26/04

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

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