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21世纪的视觉跟踪

Visual Tracking in the 21st Century
课程网址: http://videolectures.net/bmvc2012_matas_visual_tracking/  
主讲教师: Jiri Matas
开课单位: 布拉格捷克工业大学
开课时间: 2012-11-05
课程语种: 英语
中文简介:

视觉跟踪是一个古老的领域,最近发现它的活动激增。诸如检测,分段和光流等相关领域的进展以及应用程序驱动的需求以及可用计算能力的提高激发了人们的兴趣。

已发布的跟踪方法在许多方面都存在差异,例如速度,被跟踪实体模型的复杂性,假设的(几何)转换,操作模式(偶然和非因果关系),适应和学习的能力,对遮挡的鲁棒性以及关于观察者的假设。我将回顾最近出版物中使用的数据集,并显示“跟踪器空间”仍然是广阔的领域,尚有待探索的大范围。

然后,我将介绍由我和我的合作者开发的三个跟踪器速度健壮性灵活性空间中非常不同的点,它们与已发布方法的“凸包”接近:TLD跟踪器,Flock跟踪器和零偏移点跟踪器。我将重点介绍跟踪器共有的一个共同方面:预测和处理跟踪错误的机制。这种机制有助于跟踪器的鲁棒性,并将在现场进行演示。

课程简介: Visual tracking is an old area that has recently seen a surge in activity. The interest has been fueled by progress in related fields like detection, segmentation and optic flow as well as by application-driven demand and the increase in the available computing power. The published tracking methods differ in many aspects such as the speed, the complexity of the model of the tracked entity, the (geometric) transformations assumed, the mode of operation (casual and non-causal), the ability to adapt and learn, the robustness to occlusion and assumptions about the observer. I will review the dataset used in recent publications and show that the "tracker space" is still wide open with large areas to be explored. I will then present three trackers developed by me and my collaborators that operate at very different points in the speed-robustness-flexibility space that are close to the "convex hull" of published methods: the TLD tracker, the Flock-of-Trackers and the Zero-Shift-Point tracker. I will focus on a common aspect shared by the trackers: mechanisms for prediction and handling of tracking errors. Such mechanisms contribute to tracker robustness, which will be demonstrated live.
关 键 词: 视觉跟踪; 跟踪器
课程来源: 视频讲座网
数据采集: 2020-11-24:zyk
最后编审: 2020-12-30:zyk
阅读次数: 46