Finally, I got time to blog again. I have moved this post to its new location on my site and I maintain the code there afterwards. Here is the link:
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HOG introduced by (Dalal & Triggs, 2005) is a feature set for robust visual object recognition.
HOG introduced by (Dalal & Triggs, 2005) is a feature set for robust visual object recognition.
They used HOG in human detection as a test case for their experiments. They reviewed existing edge and gradient based descriptors and showed experimentally that grids of Histograms of Oriented Gradient (HOG) descriptors had better performance among existing feature sets for human detection.
They studied the influence of each stage of the computation on performance, concluding that, fine-scale gradients, fine orientation binning, relatively coarse spatial binning and high-quality local contrast normalization in overlapping descriptor blocks are all important for good results.
I have implemented this nice feature set in MATLAB and you can download it from here.
