Variational Bayesian Algorithm Based On a Wavelet For Object Tracking

سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 803

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شناسه ملی سند علمی:

TEDECE01_314

تاریخ نمایه سازی: 30 آبان 1394

چکیده مقاله:

In this paper, the wavelet-based variational Bayesian estimation theory for object tracking in noiseless video image sequence is used. Non-stationary signals such as images can be represented as a model through their wavelet coefficients. In this method, we suppose the mixture of normal matrices distribution over the wavelet coefficients and the variational Bayesian Expectation Maximization (VBEM) algorithm is implemented on the wavelet coefficients distribution. The wavelet coefficients are updated at each frame and we can apply them for tracking. Therefore, even where there is an obstacle in front of the object, or if noise exposure, or occlusion are found at the video, the algorithm is still able to track the target so that errors of detection and tracking in such cases are reduced.

کلیدواژه ها:

object tracking ، Wavelet transform ، Mixture of normal matrices distribution ، Variational Bayesian Inference

نویسندگان

Fateme Naraghi

Islamic Azad University, South Tehran Branch Tehran, Iran

Hamidreza Amindavar

Amirkabir University of Technology, Department of Electrical Engineering Tehran, Iran

Davood Gharavian

Shahid Beheshti University, Department of Electrical Engineering Tehran, Iran