A Fast HOG Descriptor Using Lookup Table and Integral Image
This work addresses the need for faster object detection in computer vision applications, though it is incremental as it builds on the existing HOG method.
The paper tackled the computational inefficiency of the HOG descriptor for object detection by introducing a modified version using a lookup table and integral image, achieving a speedup factor of 5–10.
The histogram of oriented gradients (HOG) is a widely used feature descriptor in computer vision for the purpose of object detection. In the paper, a modified HOG descriptor is described, it uses a lookup table and the method of integral image to speed up the detection performance by a factor of 5~10. By exploiting the special hardware features of a given platform(e.g. a digital signal processor), further improvement can be made to the HOG descriptor in order to have real-time object detection and tracking.