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Accession Number ADA565269
Title Parallel Flux Tensor Analysis for Efficient Moving Object Detection.
Publication Date Jul 2011
Media Count 9p
Personal Author G. Seetharaman I. Ersoy K. Palaniappan P. Kumar S. R. Davis
Abstract The flux tensor motion flow algorithm is a versatile computer vision technique for robustly detecting moving objects in cluttered scenes. The flux tensor calculation has a high computational workload consisting of 3-D spatiotemporal filtering operations combined with 3-D weighted integration operations for estimating local averages of the flux tensor matrix trace. In order to achieve efficient real-time processing of high bandwidth video streams a data parallel multicore algorithm was developed for the Cell Broadband Engine (Cell/B.E.) processor and evaluated in terms of the energy to computation efficiency compared to a fast sequential CPU implementation. Our multicore implementation is 12 to 40 times faster than the sequential version for HD video using a single PS-3 Cell/B.E. processor and is faster than realtime for a range of filter configurations and video frame sizes. We report on the power efficiency measured in terms of performance per watt for the Cell/B.E. implementation which is at least 50 times better than the sequential version.
Keywords Algorithms
Computer applications
Computer vision
High rate
Image processing
Moving targets
Parallel orientation
Parallel processing
Processing equipment
Real time
Tensor analysis
Video frames
Video signals

Source Agency Non Paid ADAS
NTIS Subject Category 72B - Algebra, Analysis, Geometry, & Mathematical Logic
62 - Computers, Control & Information Theory
Corporate Author Missouri Univ.-Columbia. Dept. of Computer Science.
Document Type Technical report
Title Note Conference paper.
NTIS Issue Number 1304
Contract Number FA8750-09-2-0198 FA8750-10-1-0182

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