Incremental Discriminative Color Object Tracker (IDCT Tracker)

This code is a Matlab implementation of IDCT tracker

This code is a Matlab implementation of IDCT tracker (Incremental Discriminative Color Object Tracker).
A test sequence "Basketball" is included so you can simply run Demo.m.
Object rectangle and center location are saved in: [Database Name]R.mat and [Database Name]C.mat.
The code was tested on Windows/Linux with MATLAB R2011a-R2013a.
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The functions are:
cntd - computes centroid
llr - computes log liklihood ratio
map - computes object map
prext - prevent rectangle from exiting frames
sarea - computes search area
shw - show
upmdl - updates model
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This code impelemts a method for tracking an object in a sequence of images given its location in the first frame. In this approach, a combination of generative and discriminative methods is used to model the object appearance. It is used to provide a right balance between being adaptive and ability to re-track the object after losing the object due to occlusion. The quantized 3D joint RGB histograms of the region within the inner rectangle and the region between the inner and outer rectangles are used as a discriminative component. The generative component is composed of the positive part of the log-likelihood ratio of the computed 3D joint RGB histograms along with an incremental color learning scheme with a forgetting factor. In every frame, after localization, discriminative component differentiates the object from its surrounding background and adds the detected object colors to the generative model. The generative model is evolved during tracking and is used to detect the object in the next frame.
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The tracking algorithm is described in the following papers:
1. A. Asvadi, H. Mahdavinataj, M. Karami and Y. Baleghi, “Online Visual Object Tracking Using Incremental Discriminative Color Learning” CSI Journal on Computer Science and Engineering (JCSE), vol. 12, no. 2 & 4 (b), pp. 16-28, 2014.
2. A. Asvadi, H. Mahdavinataj, M. Karami and Y. Baleghi, “Incremental Discriminative Color Object Tracking” Artificial Intelligence and Signal Processing, Communications in Computer and Information Science, Volume 427, Springer Verlag 2014, pp 71-81.
http://a-asvadi.ir/idct/
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Here you can see a sample video result:
https://www.youtube.com/watch?v=tMy32yix-8s