{"id":159589,"date":"2010-06-01T00:00:00","date_gmt":"2010-06-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/a-survey-of-recent-advances-in-face-detection\/"},"modified":"2018-10-16T20:04:05","modified_gmt":"2018-10-17T03:04:05","slug":"a-survey-of-recent-advances-in-face-detection","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/a-survey-of-recent-advances-in-face-detection\/","title":{"rendered":"A Survey of Recent Advances in Face Detection"},"content":{"rendered":"<div data-canvas-width=\"323.021221352\">Face detection has been one of the most studied topics in the computer vision literature. In this technical report, we survey the recent advances in face detection for the past decade. The seminal Viola-Jones face detector is first reviewed. We then survey the various techniques according to how they extract features and what learning algorithms are adopted. It is our hope that by reviewing the many existing algorithms, we will see even better algorithms developed to solve this fundamental computer vision problem.<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Face detection has been one of the most studied topics in the computer vision literature. In this technical report, we survey the recent advances in face detection for the past decade. The seminal Viola-Jones face detector is first reviewed. We then survey the various techniques according to how they extract features and what learning algorithms 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