Titlebook: Computer Vision in Human-Computer Interaction; ECCV 2006 Workshop o Thomas S. Huang,Nicu Sebe,Branislav Kisa?anin Conference proceedings 20

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Action Recognition in Broadcast Tennis Video Using Optical Flow and Support Vector Machinecise pixel displacement. To recognize the action performed by the player, support vector machine is employed to train the classifier where the concatenation of histograms is formed as the input features. Experimental results demonstrate that our method is promising by integrating with the framework of multimodal analysis in sports video.

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ALLEY

Nostalgia

Object Retrieval by Query with Sensibility Based on the KANSEI-Vocabulary Scaleevaluation of KANSEI-Vocabulary Scale by shape. In our evaluation results, we are able to retrieve object images with the most appropriate shape in term of the query’s KANSEI. Furthermore, the method achieves an average rate of 71% user’s satisfaction.

CHIDE

The Design of Implicit Interactionsssifiers detects facial features discriminately from its local neighborhood, while the inference between the layers constrains the searching space. Extensive experiments are reported to show its accuracy and robustness.

CLOUT

The Design of Implicit Interactionsscriminate between the four emotion categories. This, despite the coarse time windows that were used. Moreover, rapid processing of the signals proved to be possible. This enables tailored HCI facilitated by an emotional awareness of systems.

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0302-9743 selected from 27 submissions. They address a wide range of theoretical and application issues in human–computer interaction. There were four thematic sessions n978-3-540-34202-1978-3-540-34203-8Series ISSN 0302-9743 Series E-ISSN 1611-3349