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The luminance of a natural scene is often of high dynamic range (HDR). In this paper, we propose a new scheme to handle HDR scenes by integrating locally adaptive scene detail capture and suppressing gradient reversals introduced by the local adaptation. The proposed scheme is novel for capturing an HDR scene by using a standard dynamic range (SDR) device(More)
Both commercial and scientific applications often need to transform color images into gray-scale images, e.g., to reduce the publication cost in printing color images or to help color blind people see visual cues of color images. However, conventional color to gray algorithms are not ready for practical applications because they encounter the following(More)
Weakly supervised image segmentation is a challenging problem in computer vision field. In this paper, we present a new weakly supervised image segmentation algorithm by learning the distribution of spatially structured super pixel sets from image-level labels. Specifically, we first extract graph lets from each image where a graph let is a small-sized(More)
Emotion recognition is one of the latest challenges in intelligent human/machine communication. Most of previous work on emotion recognition focused on extracting emotions from visual or audio information separately. A novel approach is presented in this paper to recognize the human emotion which uses both visual and audio from video clips. A tripled hidden(More)
— Facial expression analogy provides computer animation professionals with a tool to map expressions of an arbitrary source face onto an arbitrary target face. In the recent past, several algorithms have been presented in the literature that aim at putting the expression analogy paradigm into practice. Some of these methods exclusively handle expression(More)