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Color images taken in low light scenes are deteriorated with noise and motion blur. The simultaneous reduction of noise and motion blur from the low-light color images is difficult because the imposed noise hinders accurate motion blur kernel estimation. To overcome this problem, we build a novel imaging system using a single sensor that captures red, green, blue (RGB) and near-infrared (NIR) images...
We propose a method for disparity estimation in stereo video. We address the problems associated with spatially-temporally-correlated disparity variations (STCDV). STCDV problems are caused by complex motions, e.g., yaw-rotation, pan-tilt-zoom camera movements, etc. The key novelty of this study is to introduce a spatio-temporal disparity hyperplane (STDH) model. The proposed STDH model represents...
In this paper, we propose a novel method for light field imaging. Previous systems are difficult to obtain multi-viewpoint images (sub-images) at the high-resolution. In order to overcome this problem, we propose a two-layer light field imaging system by using an organic photoelectric conversion film (OPCF). Our imaging system places the OPCF having the green spectral sensitivity onto the micro-lens...
We propose an appearance-based head pose estimation method that can be automatically adapted to individual scenes. Appearance-based estimation methods usually require a ground-truth dataset taken from a scene which is similar to test video sequences. However, it is almost impossible to acquire many manually-labeled head images for each scene. To address the problem, we introduce a new approach for...
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