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Facial images embed age, gender, and other rich information that is implicitly related to occupation. In this work, we advocate that occupation prediction from a single facial image is a doable research direction. We first extract visual features from multiple levels of patches and describe them by locality-constrained linear coding. To avoid the curse of dimensionality and over fitting, a boost strategy...
In this paper, we propose the Interest Meter (IM), a system making the computer conscious of user's reactions to measure user's interest and thus use it to conduct video summarization. The IM takes account of users' spontaneous reactions when they view videos. To estimate user's viewing interest, quantitative interest measures are devised based on the perspectives of attention and emotion. For estimating...
In this paper, we propose the Interest Meter (IM), a system making computer conscious of user's reactions, to measure user's interest in real time. The Interest Meter takes account of users' spontaneous reactions when users interact with computers. In this work, we analyze variations of user's eye movement, blink, head motion, and facial expression. Furthermore, we propose an algorithm to combine...
We introduce local feature points to achieve face clustering for consumer photos. After combining eigenfaces with context information like clothes, we further investigate the usage of local feature points to match face images. The relationships between face images are constructed by feature matching and then described as a graph. Outliers in the results of preliminary clustering are detected and are...
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