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Predicting attributes from face images in the wild is a challenging computer vision problem. To automatically describe face attributes from face containing images, traditionally one needs to cascade three technical blocks — face localization, facial descriptor construction, and attribute classification — in a pipeline. As a typical classification problem, face attribute prediction has been addressed...
In this paper we present our approach to use a combination of radio frequency identification (RFID) and a wireless camera sensor network to identify and track animals at a zoo. We have developed and installed 25 cameras covering the whole zoo. The cameras are totally autonomous and they are configuring themselves in a wireless ad-hoc network. At strategic locations RFID readers are deployed to identify...
Although impressive achievement has been made in the field of lip localization, there is no clear picture showing that which algorithms or methods have technical advantages over others. It is partly due to the fact that the commonly agreed evaluation methodology has not been established yet in the field. The common practice is using manual lip labelling as the ground truth for evaluation marked by...
Automatic human lip tracking is one of the key components tomany facial image analysis tasks, such as, lip-reading and emotion from lips. It has been a classical hard image analysis problem over decades. In this paper, we propose an indirect lip tracking strategy: `lipless tracking'. It is based on the observation that many of us don't have clear lips and some even don't have visible lips. The strategy...
High dynamic range (HDR) imaging has become a topic of intense research interest in the fields of computer vision and computer graphics in recent years. Commonly a HDR radiance map of a large range scene is recovered from a set of photos taken with conventional imaging equipment at different exposures. Once a HDR map has been computed, one can apply a tone mapping technique to compress the HDR luminances...
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