Titlebook: Computer Vision in Human-Computer Interaction; ICCV 2005 Workshop o Nicu Sebe,Michael Lew,Thomas S. Huang Conference proceedings 2005 Sprin

Indicative

元音

So You Want to Use a Measure of Openness?,f the action to be recognized and those of the reference database. Results, which validate the suggested approach, are presented on a base of 1662 sequences performed by several persons and categorized in eight actions. An extension of the method for the segmentation of sequences with several actions is also proposed.

BIDE

膽小懦夫

使人煩燥

Tracking Body Parts of Multiple People for Multi-person Multimodal Interfacecond hand are recognized. Pointing gesture is fused with n-best results from speech recognition taking into account the application context. The system is tested on a chess game with two users playing on a very large display.

清真寺

皮薩

Action Recognition with Global Featuresf the action to be recognized and those of the reference database. Results, which validate the suggested approach, are presented on a base of 1662 sequences performed by several persons and categorized in eight actions. An extension of the method for the segmentation of sequences with several actions is also proposed.

prolate

3D Human Action Recognition Using Spatio-temporal Motion Templatest is learned according to the Neyman-Pearson criterion. We use the learned templates to recognize actions based on .. error measurement. Results of recognizing 22 actions on a large set of motion capture sequences as well as several annotated and automatically tracked sequences show the effectiveness of the proposed algorithm.

猜忌

Real-Time Adaptive Hand Motion Recognition Using a Sparse Bayesian Classifierow that the accuracy of the classifier can be boosted from less than 40% to over 80% by re-training it using 5 newly captured samples from each gesture class. Apart from having a better adaptability, the system can work reliably in real-time and give a probabilistic output that is useful in complex motion analysis.

chalice

https://doi.org/10.1007/b117180 model similar to the pictorial structure [6] or loose-limbed model [3], the proposed efficient, dynamic BP is carried out to find the MAP of the body configuration. The experiments on tracking the body movement in meeting scenario show robustness and efficiency of the proposed algorithm.