DocumentCode :
1898091
Title :
High performance architecture for object detection in streamed videos
Author :
Zemcik, Pavel ; Juranek, Roman ; Musil, Petr ; Musil, Martin ; Hradis, Michal
Author_Institution :
Dept. of Comput. Graphics & Multimedia, Brno Univ. of Technol., Brno, Czech Republic
fYear :
2013
fDate :
2-4 Sept. 2013
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, we introduce a novel architecture of an engine for high performance multi-scale detection of objects in videos based on WaldBoost training algorithm. The key properties of the architecture include processing of streamed data and low resource consumption. We implemented the engine in FPGA and we show that it can process 640×480 pixel video streams at over 160 fps without the need of external memory. We evaluate the design on the face detection task, compare it to state of the art designs, and discuss its features and limitations.
Keywords :
face recognition; field programmable gate arrays; object detection; video streaming; FPGA; WaldBoost training algorithm; face detection task; high performance architecture; high performance multiscale detection; object detection; pixel video streams; resource consumption; streamed data processing; streamed videos; Computer architecture; Detectors; Engines; Feature extraction; Field programmable gate arrays; Object detection; Videos;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Field Programmable Logic and Applications (FPL), 2013 23rd International Conference on
Conference_Location :
Porto
Type :
conf
DOI :
10.1109/FPL.2013.6645559
Filename :
6645559
Link To Document :
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