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GTC ON-DEMAND

Computer Vision
Presentation
Media
Cascaded HOG on GPU
Speakers:
Kento Tarui
Abstract:

We propose a real time HOG based object detector implemented on GPU. To accelerate the detection process, the proposed method uses two serially-cascaded HOG detectors. The first low dimensional HOG detector discards detection windows obviously not showing target objects. It reduces the computational cost of the second high dimensional HOG detector. This method tested on 640x480 color image and the same size movie. The computation time decreases to 70ms per image. That is 4 times faster than a case of single detector. This method provides real time performance even on middle end GPUs such as GeForce GTS 250.

 
Topics:
Computer Vision, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Silicon Valley
Year:
2010
Session ID:
S102114
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