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An efficient face detection method from news images by adaptive estimation of prior probabilities and Ising search

机译:通过自适应估计的新闻图像的高效脸部检测方法和估计概率和探索搜索

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摘要

This paper presents an efficient method to detect faces from image sequences such as news or visual surveillance. The prior probabilities of the face locations in the image are adaptively estimated. The search points in the Ising search are selected depending on the estimated prior probabilities. The information obtained at previous search point ill the given image is effectively utilized through spin flip dynamics of the Ising search. If a face is found, the prior probabilities are updated with forgetting. This makes adaptation to the changes of the environment possible. The proposed search method was applied to the news images captured during about a week. It is confirmed that the proposed method is about 10 times faster than Ising search method without prior probabilities estimation.
机译:本文提出了一种有效的方法,用于检测来自图像序列的面孔,例如新闻或视觉监控。 自适应地估计图像中的面部位置的现有概率。 根据估计的先前概率选择了ISING搜索中的搜索点。 在先前搜索点生病的信息通过insing搜索的自旋触发动态有效地利用给定图像。 如果发现了一张面部,则使用遗忘概率更新现有概率。 这使得适应可能的环境变化。 所提出的搜索方法应用于在大约一周内捕获的新闻图像。 确认,该方法比在没有先验概率估计的情况下的搜索方法速度快10倍。

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