Titlebook: Affective Computing and Intelligent Interaction; First International Jianhua Tao,Tieniu Tan,Rosalind W. Picard Conference proceedings 2005

Outspoken

https://doi.org/10.1007/978-3-658-23448-5y detection together with the mean-shift and its variants like cam-shift algorithm, can achieve fast and robust tracking of the face in noisy environment, that makes it a good candidate for use with cheap cameras and real-world applications.

jovial

偶像

IOTA

嫻熟

Corporate Governance und Stakeholder-Ansatzfective postures representing 4 emotion categories using low level descriptors. We applied multivariate analysis to recognize and categorize these postures into nuances of these categories. The results obtained show that low-level posture features may be used for this purpose, leaving the naming issue to interactive processes.

CRAMP

期滿

Frank Keuper,Stefan R?der,Carl Korsukéwitzrch negative faces than to search positive faces. However, this advantage did not appear in half-element condition when negative faces as distractors, which indicated that the view that negative faces capture attention more efficiently is not always like this.

profligate

Konzeptionalisierung und Hypothesenbildung,ion to fully perspective projection by refining the scalars corresponding to the projective depths. Extensive experiments on real sequences validate the effectiveness and improvements of the proposed method.

現(xiàn)代

Contributions to Management Scienceput of MSVM(Multi-SVMs) based expression recognition model, which is introduced to perform the expression classification. Test expression images are categorized by MSVM into one of the seven basic expression subspaces. Experiment on a data set containing 500 pictures clearly shows the efficacy of the algorithm.

傀儡

Arindam Banik,Ananda Gupta,Pradip K. Bhaumik. We further extend the affect analysis into a whole image sequence by a multi-frame post integration approach over the single frame recognition results. In our experiments, the post integration based on the fusion of face and body has shown to be more accurate than the post integration based on the facial modality only.