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GTC ON-DEMAND

Video & Image Processing
Presentation
Media
SIFT Descriptor Extraction on the GPU for Large-Scale Video Analysis
Abstract:
Learn how the analysis of large-scale video data sets can be greatly accelerated by taking usage of the power of GPUs. Due to their robustness, SIFT (Scale-Invariant Feature Transform) descriptors are very popular for all sort of video analysis tasks. In this talk, we will first present an efficient GPU implementation of an interest point detector (e.g. using the DoG or LoG operator) and the extraction of SIFT descriptors around these interest points. We will compare the GPU implementation with the reference CPU implementation from the HessSIFT library in terms of runtime and quality. Furthermore, we will talk about the benefits of GPU-accelerated SIFT descriptors for applications such as near-duplicate video detection, which aims at detecting duplicates almost identical video segments in large video data sets, or linking video segments by shooting location or salient object.
 
Topics:
Video & Image Processing, Computer Vision, Media and Entertainment
Type:
Talk
Event:
GTC Silicon Valley
Year:
2014
Session ID:
S4147
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