Robust visual voice activity detection using chaos theory under illumination varying environment

Taeyup Song, Kyungsun Lee, Hanseok Ko
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引用次数: 4

Abstract

We propose a visual based voice activity detection robust in illumination changes which frequently occurs in indoor vehicle environment. By applying chaos theory, contextual change becomes chaos-like and results in complex fractal trajectories in phase space. We measure fractality in phase space from image frames and thereby robustly detect visual speech motions under illumination changes. Representative experiments demonstrate significant improvements over conventional method.
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光照变化环境下基于混沌理论的鲁棒视觉语音活动检测
我们提出了一种基于视觉的语音活动检测方法,该方法对室内车辆环境中频繁发生的光照变化具有鲁棒性。通过应用混沌理论,上下文变化变得混沌,并导致相空间中复杂的分形轨迹。我们从图像帧中测量相空间的分形,从而鲁棒地检测光照变化下的视觉语音运动。有代表性的实验表明,该方法比传统方法有显著改进。
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