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HoG Descriptor: signed 0-360 orientation bins?

asked 2015-02-09 14:29:25 -0500

verified.human gravatar image

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: http://docs.opencv.org/modules/gpu/do...). 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

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after a quick scan of the code, there indeed seems to be a hardcoded limit to 9 bins for the ocl/cuda versions of this (unrolling loops and such)

berak gravatar imageberak ( 2015-02-10 05:46:40 -0500 )edit
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I would say, are you up to the task of changing the sourcecode? If so, please do submit a PR, this would be useful for everyone. On the other hand, I did a car detector on the 9 bin 0-180 degree approach for aerial imagery and it seemed to work pretty well.

StevenPuttemans gravatar imageStevenPuttemans ( 2015-02-11 05:40:42 -0500 )edit

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answered 2015-05-12 10:14:27 -0500

sdika gravatar image

updated 2015-05-13 08:00:08 -0500

Hi,

I made a contribution to opencv for this that has just been included. If you git clone opencv, there is now a boolean variable signedGradient in HogDescriptor. set it to true...

Here is a link to the pull request: https://github.com/Itseez/opencv/pull...

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Great! Thank you for the nice addition! Do accept your answer so this look solved. MIght be good to edit your answer and add a link to the merged PR for future reference!

StevenPuttemans gravatar imageStevenPuttemans ( 2015-05-13 01:57:50 -0500 )edit
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Asked: 2015-02-09 14:29:25 -0500

Seen: 1,330 times

Last updated: May 13 '15