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Abstract:

Aerial surveillance applications using either full motion video (FMV) or Wide Area Motion Imagery (WAMI) sensors requires accurate detection and tracking algorithms. Real-world environmental conditions (atmospheric haze, smoke, fog), and long stand-off distances make detection and tracking difficult, resulting in poor detection rates and high rates of false positives. The MSER algorithm is well-suited to these conditions, but extremely slow to compute, and until recently, impractical to use. MotionDSP implemented a new, massively parallel algorithm for MSER, implemented in CUDA, which has increased performance by more than 20x, and enabled real-time performance on extremely high resolution imagery.

Aerial surveillance applications using either full motion video (FMV) or Wide Area Motion Imagery (WAMI) sensors requires accurate detection and tracking algorithms. Real-world environmental conditions (atmospheric haze, smoke, fog), and long stand-off distances make detection and tracking difficult, resulting in poor detection rates and high rates of false positives. The MSER algorithm is well-suited to these conditions, but extremely slow to compute, and until recently, impractical to use. MotionDSP implemented a new, massively parallel algorithm for MSER, implemented in CUDA, which has increased performance by more than 20x, and enabled real-time performance on extremely high resolution imagery.

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Topics:
Video & Image Processing, Signal and Audio Processing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2013
Session ID:
S3397
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