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In this work, we decompose a first-person action into verb and noun. We then study how the coupling of an action's constituent verb and noun affects the learners' ability to learn them separately and to combine them to perform recognition. We compare different information fusion methods on conventional action recognition and zero-shot learning, of which the latter is a strong indication of the feature's...
We propose a system for detecting bids for eye contact directed from a child to an adult who is wearing a point-of-view camera. The camera captures an egocentric view of the child-adult interaction from the adult's perspective. We detect and analyze the child's face in the egocentric video in order to automatically identify moments in which the child is trying to make eye contact with the adult. We...
Fingerprint identification system has been widely used in many kinds of fields such as public security, enterprise, bank and so on. And the correctness of the feature extraction directly affects the reliability of the system. After introducing fingerprint minutiae, this paper implements an algorithm for minutiae extraction based on tracing the thin ridge line, expressing the type of current point...
This paper presents an efficient method for monocular recovering and tracking 3D human pose using 3D to 2D joints correspondences. Different from previous work, its main novelty lies in several aspects: Firstly, our method does not involve any complex features, which means that it does not tend to rely on good foreground segmentation. Secondly, formulating the model as an second order cone programming...
By the guidance of attention, human visual system is able to locate objects of interest in complex scene. We propose a new visual saliency detection model for both image and video. Inspired by biological vision, saliency is defined locally. Lossy compression is adopted, where the saliency of a location is measured by the Incremental Coding Length(ICL). The ICL is computed by presenting the center...
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