The face is a rich source of information about human behavior. Available methods for coding facial displays, however, are human-observer dependent, labor intensive, and difficult to standardize. To enable rigorous and efficient quantitative measurement of facial displays, we have developed an automated method of facial display analysis. In this report, we compare the results with this automated...

In this paper, we propose a novel approach for robust skin segmentation and face similarity measure. The proposed skin segmentation is a method for integrating the chrominance components of well-known color models. The goal of the method of skin detection is to select the appropriate color model for verifying the skin pixel under different lighting conditions and various types of skin color. Th...

This paper introduces a new architecture for face detection in color images. Based on skin locus and successive detectors, the method allows high efficiency under drastically varying illumination conditions. While most color-based approaches work only if the camera was calibrated and detect faces if the features (eyes, mouth, eyebrows...) are visible and detectable, our system detects faces eve...

Multiple face tracking plays a key role in applications related to security-surveillance, human-computer interactions, video indexing etc. Existing literature in face tracking has mainly focused on facial features from a detection/recognition viewpoint. On the other hand, we believe that reasoning with detected/tracked face regions has a strong role in multiple face tracking. We propose a reaso...

Individuals differ in the intensity of exercise they prefer and the intensity they can tolerate. The purpose of this project was to develop a measure of individual differences in the preference for and tolerance of exercise intensity. The steps involved in (a) item generation and face validation, (b) exploratory factor analysis and item selection, (c) structural validation, (d) examination of t...

The face recognition ability varies across individuals. However, it remains elusive how brain anatomical structure is related to the face recognition ability in healthy subjects. In this study, we adopted voxel-based morphometry analysis and machine learning approach to investigate the neural basis of individual face recognition ability using anatomical magnetic resonance imaging. We demonstrat...

Stacking fault energy (SFE) is considered an important parameter to predict the prevalent plastic deformation mechanism in face-centered cubic (fcc) alloys. Experimental methods for determining SFE presuppose that positive. Density functional theory (DFT) a promising tool alloy compositions with low SFEs and desirable mechanical properties. For metastable fcc alloys, DFT predicts negative value...