# A Fast HOG Descriptor Using Lookup Table and Integral Image

arXiv: https://arxiv.org/abs/1703.06256 · HTML: https://mlsanity.com/paper/1703.06256/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Mar 2017.

## Built on by (most cited first, 2 of 2)

- [Image Segmentation, Compression and Reconstruction from Edge Distribution Estimation with Random Field and Random Cluster Theories](https://mlsanity.com/paper/2104.10762/) (2021)
- [Supermarket Product Detection and Recognition: Utilizing Deep Learning with Rectified Imagery](https://mlsanity.com/paper/2610.08126/) (2026)

## Abstract (arXiv)

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.