Ask Your Question

Revision history [back]

click to hide/show revision 1
initial version

HoG Descriptor: signed 0-360 orientation bins?

I am trying to use HOG descriptors together with SVM classifiers to build a car detection algorithm. Of course inspiration for this approach is the original paper by Dalal & Triggs in which they build such detector for pedestrian detection. However for pedestrian detection it is best to use 9 orientation bins 0-180 degrees, so the orientation is UNSIGNED. Unfortunately for building a good descriptor for cars I probably need SIGNED orientation bins, for example in total 18 bins in the range 0-360 degrees.

In my application I am using the standard OpenCV implementation for extracting HOG descriptors. Currently only 9 histogram orientation bins are supported (see: Is there any way to work around this limitation and easily compute SIGNED HOG descriptors?

Quote from Dalal & Triggs paper:

For humans, the wide range of clothing and background colours presum- ably makes the signs of contrasts uninformative. However note that including sign information does help substantially in some other object recognition tasks, e.g. cars, motorbikes