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CAMP
2005
IEEE

Real-Time Low Level Feature Extraction for On-Board Robot Vision Systems

10 years 3 months ago
Real-Time Low Level Feature Extraction for On-Board Robot Vision Systems
Abstract— 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 fixedpoint, data parallel implementation. Application components and their mapping details are provided in this contribution along with a detailed analysis of their performance.
Roberto Pirrone, Giuseppe Careri, F. Saverio Fabia
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where CAMP
Authors Roberto Pirrone, Giuseppe Careri, F. Saverio Fabiano, Antonio Gentile, Salvatore Gaglio
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