图 书 馆
用于相关滤波器跟踪的目标响应自适应Target Response Adaptation for Correlation Filter Tracking |
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| 课程网址: | http://videolectures.net/eccv2016_bibi_target_response/ |
| 主讲教师: | Adel Bibi |
| 开课单位: | 阿卜杜拉国王科技大学 |
| 开课时间: | 2016-10-24 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Most correlation filter (CF) based trackers utilize the circulant structure of the training data to learn a linear filter that best regresses this data to a hand-crafted target response. These circularly shifted patches are only approximations to actual translations in the image, which become unreliable in many realistic tracking scenarios including fast motion, occlusion, etc. In these cases, the traditional use of a single centered Gaussian as the target response impedes tracker performance and can lead to unrecoverable drift. To circumvent this major drawback, we propose a generic framework that can adaptively change the target response from frame to frame, so that the tracker is less sensitive to the cases where circular shifts do not reliably approximate translations. To do that, we reformulate the underlying optimization to solve for both the filter and target response jointly, where the latter is regularized by measurements made using actual translations. This joint problem has a closed form solution and thus allows for multiple templates, kernels, and multi-dimensional features. Extensive experiments on the popular OTB100 benchmark show that our target adaptive framework can be combined with many CF trackers to realize significant overall performance improvement (ranging from 3 %–13.5 % in precision and 3.2 %–13 % in accuracy), especially in categories where this adaptation is necessary (e.g. fast motion, motion blur, etc.). |
| 关 键 词: | 数据循环; 线性滤波; 目标响应 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-07-19：chenxin01 |
| 最后编审: | 2023-07-19：chenxin01 |
| 阅读次数: | 22 |