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Best open-source pedestrian detection library for commercial use?

asked 2015-08-19 05:06:11 -0600

Tommi gravatar image

Hi there,

I'm looking for the best real-time image-based people detection software that is available for commercial use, and easily integrated to ROS. So preferably C++ with a simple structure and clear documentation. I know the state-of-art in people detection; it's easily available from surveys, e.g.

image description

What I would like to have is something similar to the algorithms marked M-Q in the image. However, all seem to be shared with a non-commercial license.

Here is what I've come up so far:

  1. OpenCV HOG implementation as ROS package -- however, basic HOG is probably not very accuratehttps://github.com/angusleigh/hog_haa...
  2. SPENCER implementation -- again, just basic HOG? Plus, it's an EU project.https://github.com/spencer-project/sp...
  3. Munaro et al -- basic Haar & HOG?https://github.com/ros-industrial/hum...

As a bonus, a good tracker that is integrated with the detector would be nice, but not it's not required.

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Can you comment on why you feel they "all seem to be shared with a non-commercial license"? Some open-source licenses explicitly allow commercial use, with just the requirement that you mention the use of the those libraries / dependencies. They don't require you to make your work open source.

gvdhoorn gravatar imagegvdhoorn ( 2015-08-24 04:24:31 -0600 )edit

They explicitly mention that the code is shared for research use only.

Tommi gravatar imageTommi ( 2015-08-25 02:29:20 -0600 )edit

All of them? Are these actual open-source licenses then?

gvdhoorn gravatar imagegvdhoorn ( 2015-08-25 03:33:11 -0600 )edit

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answered 2015-09-14 03:22:20 -0600

Tommi gravatar image

I spent some time reading the FPDW and VeryFast papers. The conclusion is that they are mostly performance optimizations and small tweaks, while the fundamental detector is still HOG. Also, the classifier (SVM, NN, decision forest) does not make a huge difference. Therefore, I decided to go with HOG+SVM because it's fast and simple, and I found a good implementation from http://dlib.net . Example: http://blog.dlib.net/2014/02/dlib-186... Dlib uses an improved version of HOG, by Felzenszwalb et al. Also, performance _should_ be better than OpenCV.

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Hi Tommi, thanks a lot for your recommendation. How was you pedestrian detection using dlib? Is it good? Can you share something about the result? I made a brief survey on c++ libraries for pedestrian detection but so far dlib seems to be a feasible one that is better than OpenCV...

phivu123 gravatar imagephivu123 ( 2017-06-12 22:41:16 -0600 )edit

... but very few users share the result on this.

phivu123 gravatar imagephivu123 ( 2017-06-12 22:46:50 -0600 )edit

I'm really happy with dlib, it's a good quality library. Nowadays you'd get a better performance with Deep Neural Networks but with a bigger computational cost in general.

Tommi gravatar imageTommi ( 2017-06-13 00:22:50 -0600 )edit

That sounds great, do you know any workable c++ library that supports deep neural network training for pedestrian detection, or can dlib do that? Thanks!

phivu123 gravatar imagephivu123 ( 2017-06-13 01:23:16 -0600 )edit

I don't know but you might want to look into Python libraries instead.

Tommi gravatar imageTommi ( 2017-06-13 03:01:38 -0600 )edit
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answered 2016-12-18 14:14:59 -0600

We just developed a commercial-grade implementation of several pedestrian detectoer, such as HOG, DPM, ICF and ACF. A licence of this software code is available via KU Leuven EAVISE: www.eavise.be

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Asked: 2015-08-19 05:03:23 -0600

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Last updated: Sep 14 '15