文件名称:Matlab_STCv0
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- 上传时间：
- 2016-04-22
- 文件大小：
- 6.87mb
- 下载次数：
- 0次
- 提 供 者：
- 老*
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
时空上下文视觉跟踪（STC）算法的解读与代码复现
该论文提出一种简单却非常有效的视觉跟踪方法。更迷人的一点是，它速度很快，原作者实现的Matlab代码在i7的电脑上达到350fps。
该论文的关键点是对时空上下文（Spatio-Temporal Context）信息的利用。主要思想是通过贝叶斯框架对要跟踪的目标和它的局部上下文区域的时空关系进行建模，得到目标和其周围区域低级特征的统计相关性。然后综合这一时空关系和生物视觉系统上的focus of attention特性来评估新的一帧中目标出现位置的置信图，置信最大的位置就是我们得到的新的一帧的目标位置。另外，时空模型的学习和目标的检测都是通过FFT（傅里叶变换）来实现，所以学习和检测的速度都比较快。-Space-time visual tracking context (STC) algorithm for interpretation and code reuse the existing paper proposes a simple but very effective visual tracking method. More attractive is that it is fast, Matlab codes to achieve the original author reaches 350fps on i7 computer. The key point of the paper is a space-time context (Spatio-Temporal Context) access to information. The main idea is to be tracked through a Bayesian fr a mework of goals and temporal relationship between its local context area is modeled to obtain objective and its surrounding area statistical correlation between low-level features. Then focus on the relationship between the biological and the integrated vision system to uate the spatial and temporal characteristics of attention of a new target position occurs confidence map, is the new position of maximum confidence of an objective position we get. In addition, the study and detection of target space-time model through FFT (Fourier transform) to achieve, so learni
该论文提出一种简单却非常有效的视觉跟踪方法。更迷人的一点是，它速度很快，原作者实现的Matlab代码在i7的电脑上达到350fps。
该论文的关键点是对时空上下文（Spatio-Temporal Context）信息的利用。主要思想是通过贝叶斯框架对要跟踪的目标和它的局部上下文区域的时空关系进行建模，得到目标和其周围区域低级特征的统计相关性。然后综合这一时空关系和生物视觉系统上的focus of attention特性来评估新的一帧中目标出现位置的置信图，置信最大的位置就是我们得到的新的一帧的目标位置。另外，时空模型的学习和目标的检测都是通过FFT（傅里叶变换）来实现，所以学习和检测的速度都比较快。-Space-time visual tracking context (STC) algorithm for interpretation and code reuse the existing paper proposes a simple but very effective visual tracking method. More attractive is that it is fast, Matlab codes to achieve the original author reaches 350fps on i7 computer. The key point of the paper is a space-time context (Spatio-Temporal Context) access to information. The main idea is to be tracked through a Bayesian fr a mework of goals and temporal relationship between its local context area is modeled to obtain objective and its surrounding area statistical correlation between low-level features. Then focus on the relationship between the biological and the integrated vision system to uate the spatial and temporal characteristics of attention of a new target position occurs confidence map, is the new position of maximum confidence of an objective position we get. In addition, the study and detection of target space-time model through FFT (Fourier transform) to achieve, so learni
(系统自动生成,下载前可以参看下载内容)
下载文件列表
data
....\0001.jpg
....\0002.jpg
....\0003.jpg
....\0004.jpg
....\0005.jpg
....\0006.jpg
....\0007.jpg
....\0008.jpg
....\0009.jpg
....\0010.jpg
....\0011.jpg
....\0012.jpg
....\0013.jpg
....\0014.jpg
....\0015.jpg
....\0016.jpg
....\0017.jpg
....\0018.jpg
....\0019.jpg
....\0020.jpg
....\0021.jpg
....\0022.jpg
....\0023.jpg
....\0025.jpg
....\0026.jpg
....\0027.jpg
....\0028.jpg
....\0029.jpg
....\0030.jpg
....\0031.jpg
....\0032.jpg
....\0033.jpg
....\0034.jpg
....\0035.jpg
....\0036.jpg
....\0037.jpg
....\0038.jpg
....\0039.jpg
....\0040.jpg
....\0041.jpg
....\0042.jpg
....\0043.jpg
....\0044.jpg
....\0045.jpg
....\0046.jpg
....\0047.jpg
....\0048.jpg
....\0049.jpg
....\0050.jpg
....\0051.jpg
....\0052.jpg
....\0053.jpg
....\0054.jpg
....\0055.jpg
....\0056.jpg
....\0057.jpg
....\0058.jpg
....\0059.jpg
....\0060.jpg
....\0061.jpg
....\0062.jpg
....\0063.jpg
....\0064.jpg
....\0065.jpg
....\0066.jpg
....\0067.jpg
....\0068.jpg
....\0069.jpg
....\0070.jpg
....\0071.jpg
....\0072.jpg
....\0073.jpg
....\0074.jpg
....\0075.jpg
....\0076.jpg
....\0077.jpg
....\0078.jpg
....\0079.jpg
....\0080.jpg
....\0081.jpg
....\0082.jpg
....\0083.jpg
....\0084.jpg
....\0085.jpg
....\0086.jpg
....\0087.jpg
....\0088.jpg
....\0089.jpg
....\0090.jpg
....\0091.jpg
....\0092.jpg
....\0093.jpg
....\0094.jpg
....\0095.jpg
....\0096.jpg
....\0097.jpg
....\0098.jpg
....\0099.jpg
....\0100.jpg