6533b7d8fe1ef96bd1269906

RESEARCH PRODUCT

Real-time low level feature extraction for on-board robot vision systems

R. PirroneG. CareriF.s. FabianoA. GentileS. Gaglio

subject

PixelComputer sciencebusiness.industryComputationvision systems real-timeFeature extractionNull (SQL)Computer architectureEmbedded systemRobotSIMDArchitectureUnconventional computingbusiness

description

Robot vision systems notoriously require large computing capabilities, rarely available on physical devices. Robots have limited embedded hardware, and almost all sensory computation is delegated to remote machines. Emerging gigascale integration technologies offer the opportunity to explore alternative computing architectures that can deliver a significant boost to on-board computing when implemented in embedded, reconfigurable devices. This paper explores the mapping of low level feature extraction on one such architecture, the Georgia Tech SIMD Pixel Processor (SIMPil). The Fast Boundary Web Extraction (fBWE) algorithm is adapted and mapped on SIMPil as a fixed-point, data parallel implementation. Application components and their mapping details are provided in this contribution along with a detailed analysis of their performance.

http://www.scopus.com/inward/record.url?eid=2-s2.0-28444479138&partnerID=MN8TOARS