Motion segmentation method based on mixtures-of-dynamic-textures-based spatiotemporal saliency detection

A dynamic texture and motion segmentation technology, applied in image analysis, image data processing, instruments, etc., can solve the problem that single-mode dynamic texture cannot accurately describe the real scene, and achieve the effect of improving accuracy, obvious effect, and obvious interference suppression

Inactive Publication Date: 2012-06-20
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

However, this method is based on a single-modal dynamic texture model. In real scenes, dynamic backgrounds are often not single-modal, but multi-modal. Single-modal dynamic textures cannot accurately describe real scenes.

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  • Motion segmentation method based on mixtures-of-dynamic-textures-based spatiotemporal saliency detection
  • Motion segmentation method based on mixtures-of-dynamic-textures-based spatiotemporal saliency detection
  • Motion segmentation method based on mixtures-of-dynamic-textures-based spatiotemporal saliency detection

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Embodiment Construction

[0031] The embodiment of the present invention will be described in detail below. The embodiment is implemented on the premise of the technical solution of the present invention, and a detailed operation process is given.

[0032] The present invention provides a motion segmentation method based on MDT space-time saliency detection, and the process of the method is:

[0033] Given a video sequence V, each element is l(m,n,t)∈L=R 3 , the dimension of the state space x is n, and the size of the center window is n c pixels, the structural window size used to model dynamic textures is n p , the time window is τ frame;

[0034] Do the following for each pixel of each frame:

[0035] take center window of size n c ×n c×τ, the neighborhood window size is 4n c ×4n c ×τ;

[0036] Modeling window n with texture p ×n p ×τ overlays the center window up and move, as the texture sampling of the central area, and then use the EM algorithm to estimate its texture parameters. ...

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Abstract

The invention discloses a motion segmentation method based on mixtures-of-dynamic-textures-based spatiotemporal saliency detection. The method comprises the following steps of: 1, modeling a background by adopting mixtures of dynamic textures; 2, defining a spatiotemporal saliency discrimination function by utilizing a Kullback-Leibler (KL) divergence, and calculating a saliency map; and 3, processing a saliency threshold value to obtain a motion segmentation result. By the method, a motional object can be accurately segmented in a complex environment with a highly-dynamic background and a motional camera; and compared with the conventional method, the invention greatly improves complex scene processing and noise suppression, has relatively higher robustness and can be applied to various complex motion scenes.

Description

technical field [0001] The present invention relates to a moving target segmentation method in the technical field of information processing, in particular to a motion segmentation method based on mixed dynamic texture (Mixtures of Dynamic Textures, MDT) spatiotemporal saliency detection. Background technique [0002] The task of motion segmentation is to extract moving objects as completely as possible from a video sequence. There are two difficulties in this task: (1) high dynamic background, motion segmentation often encounters situations where the background is also moving, such as swaying branches, rain and snow, pedestrians, water waves, etc.; (2) camera motion, in many practical applications , the camera is not fixed. Traditional methods usually make the following assumptions to simplify the problem: (1) the camera is stationary; or (2) the camera motion parameters can be obtained or calculated; or (3) the background satisfies a given model, such as a Gaussian mixtur...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/20G06T7/215
Inventor 周文明姚莉秀杨杰
Owner SHANGHAI JIAO TONG UNIV
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