We present a novel approach for real-time rendering of translucent surfaces.

No abstract

Face detection often plays the first step in various visual applications. Large variants of facial deformations due to head movements and facial expression make it difficult to identify appropriate face region. In this paper, a robust real-time face alignment system, including facial landmarks detection and face rectification, is proposed. A facial landmarks detection model based on regression tree is utilized in the proposed system. In face rectification framework, 2-D geometrical analysis based on pitch, yaw and roll movements is designed to solve the misalignment problem in face detection. The experiments on the two datasets verify the performance significantly improved by the proposed method in the facial recognition task and outperform than those obtained by other alignment methods. Furthermore, the proposed method can achieve robust recognition results even if the amount of training images is not large.

Human beings spend approximately one third of their lives sleeping. Conventionally, to evaluate a subjects sleep quality, all-night polysomnogram (PSG) readings are taken and scored by a well-trained expert. The development of an automatic sleep-staging system that does not rely upon mounting a bulky PSG or EEG recorder on the head will enable physiological computing systems (PhyCS) to progress toward easy sleep and comfortable monitoring. In this paper, an electrooculogram (EOG)-based sleep scoring system is proposed. Compared to PSG or EEG recordings, EOG has the advantage of easy placement, and can be operated by the user individually. The proposed method was found to be more than 83% accurate when compared with the manual scorings applied to sixteen subjects. In addition to sleep-quality evaluation, the proposed system encompasses adaptive brightness control of light according to online monitoring of the users sleep stages. The experiments show that the EOG-based sleep scoring system is a practicable solution for home-use sleep monitoring due to the advantages of comfortable recording and accurate sleep staging.