A multi-feature tracking algorithm enabling adaptation to context variations
Duc Phu Chau,Francois Bremond,Monique Thonnat +2 more
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TLDR
A robust tracking algorithm based on a feature pool, a supervised learning scheme to learn feature weights for each context, and a combination of color covariance and dominant color features with spatial pyramid distance to manage the case of object occlusion are proposed.Abstract:
We propose in this paper a tracking algorithm which is able to adapt itself to different scene contexts. A feature pool is used to compute the matching score between two detected objects. This feature pool includes 2D, 3D displacement distances, 2D sizes, color histogram, histogram of oriented gradient (HOG), color covariance and dominant color. An offline learning process is proposed to search for useful features and to estimate their weights for each context. In the online tracking process, a temporal window is defined to establish the links between the detected objects. This enables to find the object trajectories even if the objects are misdetected in some frames. A trajectory filter is proposed to remove noisy trajectories. Experimentation on different contexts is shown. The proposed tracker has been tested in videos belonging to three public datasets and to the Caretaker European project. The experimental results prove the effect of the proposed feature weight learning, and the robustness of the proposed tracker compared to some methods in the state of the art. The contributions of our approach over the state of the art trackers are: (i) a robust tracking algorithm based on a feature pool, (ii) a supervised learning scheme to learn feature weights for each context, (iii) a new method to quantify the reliability of HOG descriptor, (iv) a combination of color covariance and dominant color features with spatial pyramid distance to manage the case of object occlusion.read more
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References
More filters
Journal ArticleDOI
A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
Yoav Freund,Robert E. Schapire +1 more
TL;DR: The model studied can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting, and it is shown that the multiplicative weight-update Littlestone?Warmuth rule can be adapted to this model, yielding bounds that are slightly weaker in some cases, but applicable to a considerably more general class of learning problems.
Journal ArticleDOI
Object tracking: A survey
TL;DR: The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends to discuss the important issues related to tracking including the use of appropriate image features, selection of motion models, and detection of objects.
Proceedings ArticleDOI
The pyramid match kernel: discriminative classification with sets of image features
Kristen Grauman,Trevor Darrell +1 more
TL;DR: A new fast kernel function is presented which maps unordered feature sets to multi-resolution histograms and computes a weighted histogram intersection in this space and is shown to be positive-definite, making it valid for use in learning algorithms whose optimal solutions are guaranteed only for Mercer kernels.
Proceedings ArticleDOI
Evaluation campaigns and TRECVid
TL;DR: An introduction to information retrieval (IR) evaluation from both a user and a system perspective is given, high-lighting that system evaluation is by far the most prevalent type of evaluation carried out.
Book ChapterDOI
A Metric for Covariance Matrices
TL;DR: In this article, the distance coming from a canonical invariant Riemannian metric on the space Sym + (n, ℝ) of real symmetric positive definite matrices is defined.