Title :
A Support Vector Machine based pedestrian recognition system on resource-limited hardware architectures
Author :
Ghio, Alessandro ; Pischiutta, Stefano
Author_Institution :
Univ. of Genoa (Italy), Genoa
Abstract :
We present here a hardware-friendly structure for the support vector machine (SVM), useful to implement its feedforward phase on resource limited devices, such as field programmable gate arrays (FPGAs), on which a floating-point unit is seldom available. We tested our proposal using an artificial machine-vision benchmark dataset for automotive applications.
Keywords :
automotive electronics; computer vision; feedforward; field programmable gate arrays; pattern recognition; support vector machines; FPGA; SVM; artificial machine-vision benchmark dataset; automotive applications; feedforward phase; field programmable gate arrays; hardware-friendly structure; pedestrian recognition system; resource limited devices; resource-limited hardware architectures; support vector machine; Automotive applications; Benchmark testing; Digital arithmetic; Field programmable gate arrays; Hardware; Helium; Kernel; Phased arrays; Proposals; Support vector machines;
Conference_Titel :
Research in Microelectronics and Electronics Conference, 2007. PRIME 2007. Ph.D.
Conference_Location :
Bordeaux
Print_ISBN :
978-1-4244-1000-2
Electronic_ISBN :
978-1-4244-1001-9
DOI :
10.1109/RME.2007.4401836
