Unconstrained Face Recognition with User Interaction

Face recognition in unconstrained environment is very challenging due to the variations in facial expression, face pose, light condition and occlusion (e.g. eye glasses or hair). A recent project led by Dr. Learned-Miller at University of Massachusetts, Amherst, published the test results on 13,000 images of faces collected from web. The results are described in an ROC curve. At 10% false positive rate, the best true position rate (recognition rate) is around 67%. That is, in 100 face images for one person, only 67 faces are correctly recognized as this person; in 100 faces images of other persons, 10 faces are incorrectly recognized as this person. Therefore there is still big gap between this performance and the requirements of security applications, for example, access control. But are these results useful for other practical applications?  

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VeinViewer: Computational Imaging Makes Needlesticks Easier

Have you experienced being poked several times for your nurse to find your vein for an IV insertion?

Blood collection from children is an extremely difficult task because of their thick skin. The VeinViewer by Luminetx® can help. The VeinViewer utilizes near infrared (NIR) imaging and image processing technologies to assist health care professionals to find veins easier. 

The following video is a brief report on VeinViewer from ABC.
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Smart Video Thumbnail Comes to YouTube

After you upload a video to YouTube, one thumbnail image will be displayed linking to your video. A thumbnail image is usually small but it is very important. It delivers the first visual impression of your video to audience browsing millions of videos on the web. 

How does YouTube generate thumbnails for videos?

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