Special Section on High-Performance Computing in Applied Remote Sensing: Part 2

Fast motion detection from airborne videos using graphics processing unit

[+] Author Affiliations
Kui Liu, Ben Ma, Qian Du

Mississippi State University, Department of Electrical and Computer Engineering, Mississippi State, Mississippi 39762

Genshe Chen

DCM Research Resources LLC, Germantown, Maryland 20874

J. Appl. Remote Sens. 6(1), 061505 (May 10, 2012). doi:10.1117/1.JRS.6.061505
History: Received September 2, 2011; Revised January 20, 2012; Accepted March 19, 2012
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Abstract.  In our previous work, we proposed a joint optical flow and principal component analysis (PCA) approach to improve the performance of optical flow based detection, where PCA is applied on the calculated two-dimensional optical flow image, and motion detection is accomplished by a metric derived from the two eigenvalues. To reduce the computational time when processing airborne videos, parallel computing using graphic processing unit (GPU) is implemented on NVIDIA GeForce GTX480. Experimental results demonstrate that our approach can efficiently improve detection performance even with dynamic background, and processing time can be greatly reduced with parallel computing on GPU.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Kui Liu ; Ben Ma ; Qian Du and Genshe Chen
"Fast motion detection from airborne videos using graphics processing unit", J. Appl. Remote Sens. 6(1), 061505 (May 10, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.061505


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