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Representation learning is a fundamental challenge for feature selection and plays an important role in applications such as dimension reduction, data mining and object recognition. Traditional linear representation methods, such as principal component analysis (PCA), independent component analysis (ICA) and linear discriminate analysis (LDA), have good performance on certain applications based on...
Human-machine interaction still lacks smoothness and naturalness despite the widespread utilization of intelligent systems and emotive agents. In order to improve the interaction, this work proposes an approach to estimate user's interest based on the relationships between dynamics of user's eye movements, more precisely the endogenous control mode of saccades, and machine's proactive visual content...
Facial aging has been only partially studied in the past and mostly in a qualitative way. This paper presents a novel approach to the estimation of facial aging aimed to the quantitative evaluation of the changes in facial appearance over time. In particular, the changes both in face shape and texture, due to short-time aging, are considered. The developed framework exploits the concept of ldquodistinctivenessrdquo...
In this paper, we investigate a recently proposed efficient subspace learning method, Spectral Regression Discriminant Analysis (SRDA), and its kernel version SRKDA for head pose estimation. One important unsolved issue of SRDA is how to automatically determine an appropriate regularization parameter. The parameter, which was empirically set in the existing work, has great impact on its performance...
Landmark labeling of training images is essential for many learning tasks in computer vision, such as object detection, tracking, and alignment. Image labeling is typically conducted manually, which is both labor-intensive and error-prone. To improve this process, this paper proposes a new approach to estimate a set of landmarks for a large image ensemble with only a small number of manually labeled...
The application of action recognition algorithms onto driving safety systems is still an open area of research. In terms of driving safety, identification of head movements present more significant information in comparison to other actions of the driver. Therefore, in this study, we developed a cylindrical model based head pose estimator to track drivers' head movements. The experiments indicate...
Biometrics has carved an important place in the field of identification and authentication. Identification in biometrics includes various applications like face recognition. There are scads of work done in the area of face recognition but we feel that there is not much of work has been done in the field of age determination. The age determination technique is useful to determine the age of an unknown...
The demand for information services considering personal preferences is increasing. In this paper, we propose a system for automatically acquiring personal preferences from TV viewerpsilas behaviors. Our system firstly extracts intervals of interest and estimates the interest degree for each extracted interval based on the temporal patterns in facial changes by Hidden Markov Models (HMMs). Then, the...
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