Accession Number:

ADA565269

Title:

Parallel Flux Tensor Analysis for Efficient Moving Object Detection

Descriptive Note:

Conference paper

Corporate Author:

MISSOURI UNIV-COLUMBIA DEPT OF COMPUTER SCIENCE

Report Date:

2011-07-01

Pagination or Media Count:

9.0

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 CellB.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 CellB.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 CellB.E. implementation which is at least 50 times better than the sequential version.

Subject Categories:

  • Theoretical Mathematics
  • Cybernetics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE