1. Presentation 3 Ruben Villegas Period: 05/31/2012 – 06/03/2012

2. Histogram of Oriented Gradients for Human Detection

3. The Human Detection Problem Humans have extremities that have a wide range of motion. Humans can adopt different poses and have variable appearances. A lot harder than detecting objects which have a fixed shape.

4. Overview Based on evaluating well-normalized local histograms of image gradient orientations in a dense grid. The image is divided into small spatial regions For each cell get a histogram of gradient directions or edge orientations and Contrast normalize blocks of these cells. This captures edge or gradient structure that is very characteristic of the local shape. Translations of rotations make little difference if they are smaller than the local orientation bin size.

5. Process