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GTC ON-DEMAND

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Abstract:
We'll talk about the evolution of the Connected Component Labeling (CCL) algorithm for GPUs and introduce a new algorithm for both CCL and connected-component analysis. CCL is a central algorithm for low- and high-level image processing used computer vision applications such as OCR, motion detection, and tracking. Formerly After an era on single-core processors, where many sequential algorithms were developed and few codes were released, new parallel algorithms were developed on multi-core processors, SIMD processors and GPUs. We'll discuss how a benchmark on an NVIDIA Jetson TX2 shows that the new algorithm is up to 2.7 times faster than the state-of-the-art and can reach a processing rate of 200 fps for a resolution of 2048x2048.
We'll talk about the evolution of the Connected Component Labeling (CCL) algorithm for GPUs and introduce a new algorithm for both CCL and connected-component analysis. CCL is a central algorithm for low- and high-level image processing used computer vision applications such as OCR, motion detection, and tracking. Formerly After an era on single-core processors, where many sequential algorithms were developed and few codes were released, new parallel algorithms were developed on multi-core processors, SIMD processors and GPUs. We'll discuss how a benchmark on an NVIDIA Jetson TX2 shows that the new algorithm is up to 2.7 times faster than the state-of-the-art and can reach a processing rate of 200 fps for a resolution of 2048x2048.  Back
 
Topics:
Computer Vision, Performance Optimization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9111
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