1 research outputs found
Visual Object Tracking Approach Based on Wavelet Transforms
In this Thesis, a new visual object tracking (VOT) approach is proposed to overcome the main
challenging problem encountered within the existing approaches known as the significant
appearance changes which is due mainly to the heavy occlusion and illumination variations.
Indeed, the proposed approach is based on combining the deep convolutional neural networks
(CNN), the histograms of oriented gradients (HOG) features, and the discrete wavelet packet
transform to ensure the implementation of three ideas. Firstly, solving the problem of
illumination variation by incorporating the coefficients of the image discrete wavelet packet
transform instead of the image template to handle the case of images with high saturation in
the input of the used CNN, whereas the inverse discrete wavelet packet transform is used at
the output for extracting the CNN features. Secondly, by combining four learned correlation
filters with convolutional features, the target location is deduced using multichannel
correlation maps at the CNNs output. On the other side, the maximum value of the resulting
maps from correlation filters with convolutional features produced by HOG feature of the
image template previously obtained are calculated and which are used as an updating
parameter of the correlation filters extracted from CNN and from HOG where the major aim
is to ensure long-term memory of target appearance so that the target item may be recovered
if tracking fails. Thirdly, to increase the performance of HOG, the coefficients of the discrete
packet wavelet transform are employed instead of the image template. Finally, for the
validation and the evaluation of the proposed tracking approach performance based on
specific performance metrics in comparison to the state-of-the-art counterparts, extensive
simulation experiments on benchmark datasets have been conducted out, such as OTB50,
OTB100 , TC128 ,and UAV20. The obtained results clearly prove the validity of the proposed
approach in solving the encountered problems of visual object tracking in almost the
experiment cases presented in this thesis compared to other existing tracking approaches