OpenTLD-master
所属分类：视频捕捉采集剪辑
开发工具：Others
文件大小：9216KB
下载次数：55
上传日期：2013-04-27 10:27:58
上 传 者：
YorkLee
说明： TLD(Tracking-Learning-Detection)是英国萨里大学的一个捷克籍博士生Zdenek Kalal在其攻读博士学位期间提出的一种新的单目标长时间（long term tracking）跟踪算法。该算法与传统跟踪算法的显著区别在于将传统的跟踪算法和传统的检测算法相结合来解决被跟踪目标在被跟踪过程中发生的形变、部分遮挡等问题。同时，通过一种改进的在线学习机制不断更新跟踪模块的“显著特征点”和检测模块的目标模型及相关参数，从而使得跟踪效果更加稳定、鲁棒、可靠。
(TLD (Tracking-Learning-Detection) is the University of Surrey in the United Kingdom a Czech citizen doctoral Zdenek Kalal in its doctorate during a new target for a long time (long term tracking) tracking algorithm. The significant difference is that the algorithm with the traditional tracking algorithm combining the traditional tracking algorithm and traditional detection algorithm to solve the occurrence of deformation of the target being tracked in the tracking process, the partial occlusion problem. The same time, through an improved online learning mechanism constantly updated tracking module " significant feature points and the goal of the detection module model and related parameters, so that the tracking performance is more stable, robust and reliable.)
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LICENSE (35146, 2011-04-17)
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TLD (aka Predator)
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TLD is an algorithm for tracking of unknown objects in unconstrained video streams. The object of interest is defined by a bounding box in a single frame. TLD simultaneously tracks the object, learns its appearance and detects it whenever it appears in the video.
1. License
This source code is released under the GPL license version 3.0. For alternative licensing options contact the main author: zdenek.kalal@gmail.com.
2. Project website
You can find more information about TLD at: http://info.ee.surrey.ac.uk/Personal/Z.Kalal/tld.html. This includes the description of TLD, links to research papers, posters and the licensing options.
3. Wiki
Many questions regarding TLD are already answered at the following wiki: https://github.com/zk00006/OpenTLD/wiki. These questions include installation and common errors. Make sure to check the wiki first.
4. Discussion group
If you do not find your answer in the wiki, ask the question directly at the following discussion group: http://groups.google.com/group/opentld. There are currently around 250 participants and it is likely you will get the answer soon.
5. Feedback
Predator learns from its errors; let us do the same in this community! Therefore, if you get an answer that was not covered in the wiki, please update the wiki so that other people do not have to face the same problem. The wiki is freely editable at the moment.
6. Citations
In case you use TLD in an academic work, please cite the following paper:
@article{Kalal2010,
author = {Kalal, Z and Matas, J and Mikolajczyk, K},
journal = {Conference on Computer Vision and Pattern Recognition},
title = {{P-N Learning: Bootstrapping Binary Classifiers by Structural Constraints}},
year = {2010}
}
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(c) 2011 Zdenek Kalal, zdenek.kalal@gmail.com
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