Illumination invariant Mean-shift tracking

@article{Phadke2013IlluminationIM,
  title={Illumination invariant Mean-shift tracking},
  author={G. Phadke and R. Velmurugan},
  journal={2013 IEEE Workshop on Applications of Computer Vision (WACV)},
  year={2013},
  pages={407-412}
}
  • G. Phadke, R. Velmurugan
  • Published 2013
  • Computer Science
  • 2013 IEEE Workshop on Applications of Computer Vision (WACV)
Visual tracking is a critical task in surveillance and activity analysis. One of the major issues in visual target tracking is variations in illumination. In this paper, we propose a novel algorithm based on discrete cosine transform (DCT) to handle illumination variations, since illumination variations are mainly reflected in the low-frequency band. For instance, low illumination in a frame leads to low value DC coefficient as vias versa. We modify DC coefficient to achieve illumination… Expand
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References

SHOWING 1-10 OF 15 REFERENCES
Illumination invariant object tracking based on multiscale phase
  • D. Zang
  • Mathematics, Computer Science
  • 2010 IEEE International Conference on Image Processing
  • 2010
TLDR
It is proved that the proposed illumination invariant object tracking approach outperforms the mean shift tracker under the high lighting change environment. Expand
Robust mean-shift tracking with corrected background-weighted histogram
The background-weighted histogram (BWH) algorithm proposed by Comaniciu et al. attempts to reduce the interference of background in target localisation in mean-shift tracking. However, the authorsExpand
BigBackground-Based Illumination Compensation for Surveillance Video
TLDR
BigBackground is introduced, which is a model for representing large, persistent scene features based on chromatic self-similarity that is found to comprise 50% to 90% of surveillance scenes and to decrease improper false-positive classification of background pixels. Expand
Real-time tracking of non-rigid objects using mean shift
TLDR
The theoretical analysis of the approach shows that it relates to the Bayesian framework while providing a practical, fast and efficient solution for real time tracking of non-rigid objects seen from a moving camera. Expand
Avoiding false positive due to flashlights in shot detection using illumination suppression algorithm
Existence of flashlights in videos leads to false detection of scene change. Many algorithms have been suggested to either detect the flashlight or differentiate between flashlight and abruptExpand
Spatiotemporal Oriented Energy Features for Visual Tracking
TLDR
A novel feature set for visual tracking that is derived from "oriented energies" is presented, using energy measures to capture a target's multiscale orientation structure across both space and time, yielding a rich description of its spatiotemporal characteristics. Expand
Integrating Color and Shape-Texture Features for Adaptive Real-Time Object Tracking
TLDR
The standard mean-shift tracking algorithm is extended to an adaptive tracker by selecting reliable features from color and shape-texture cues according to their descriptive ability, which makes the tracker more robust. Expand
PFT: A protocol for evaluating video trackers
  • T. Nawaz, A. Cavallaro
  • Computer Science
  • 2011 18th IEEE International Conference on Image Processing
  • 2011
TLDR
A protocol to evaluate the performance of tracking algorithms that tests video trackers using a set of trials and a pre-defined set of sequences and that enables objective and reproducible performance evaluation of tracker performance using ground truth information is presented. Expand
AUTOMATIC IMAGE EQUALIZATION AND CONTRAST ENHANCEMENT USING GAUSSIAN MIXTURE MODELING
In this paper an adaptive image equalization algorithm is introduced it automatically enhances the contrast in an input image. It uses the Gaussian mixture model to model the image gray-levelExpand
An efficient adaptive fusion scheme for multifocus images in wavelet domain using statistical properties of neighborhood
TLDR
A novel fusion rule which can efficiently fuse multifocus images in wavelet domain by taking weighted average of pixels, which significantly increases the quality of the fused image, both visually and in terms of quantitative parameters, especially sharpness with minimum fusion artifacts. Expand
...
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