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连续手语电视广播的自动高效长期手臂和手部跟踪Automatic and Efficient Long Term Arm and Hand Tracking for Continuous Sign Language TV Broadcasts |
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| 课程网址: | http://videolectures.net/bmvc2012_pfister_sign_language/ |
| 主讲教师: | Tomas Pfister |
| 开课单位: | 牛津大学 |
| 开课时间: | 2012-10-09 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present a fully automatic arm and hand tracker that detects joint positions over continuous sign language video sequences of more than an hour in length. Our framework replicates the state-of-the-art long term tracker by Buehler et al. (IJCV 2011), but does not require the manual annotation and, after automatic initialisation, performs tracking in real-time. We cast the problem as a generic frame-by-frame random forest regressor without a strong spatial model.\\ Our contributions are (i) a co-segmentation algorithm that automatically separates the signer from any signed TV broadcast using a generative layered model; (ii) a method of predicting joint positions given only the segmentation and a colour model using a random forest regressor; and (iii) demonstrating that the random forest can be trained from an existing semi-automatic, but computationally expensive, tracker.\\ The method is applied to signing footage with changing background, challenging imaging conditions, and for different signers. We achieve superior joint localisation results to those obtained using the method of Buehler et al. |
| 关 键 词: | 全自动手臂; 手动跟踪器; 手语视频 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-01-31：nkq |
| 阅读次数: | 47 |