而前面一项是部件实际所在的位置.PPT

A Discriminatively Trained, Multiscale, Deformable Part Model 讲解人: 郑伟 提纲 作者信息 相关文章 摘要内容 文章的内容 可变形部件建模 可变形部件匹配 建立目标函数 求解目标函数 数据发掘利用难样本 训练流程 HOG特征表示 后处理 实验结果 讨论 作者信息 Pedro Felzenszwalb Associate Professor at Department of Computer Science, University of Chicago Courses: AI, CV, statistical model Professional activities：AC (ICCV, CVPR, ECCV), AE(PAMI), EB(IJCV) David McAllester Professor and Chief Academic Officer, Toyota Technological Institute at Chicago AAAI, fellow Collaborated with Peter Bartlett, Robert E. Schapire Deva Ramanan Assistant Professor, Department of Computer Science , University of California at Irvine PhD from UC Berkeley, advised by David Forsyth Marr Prize 2009:Discriminative models for multi-class object layout 提纲 作者信息 相关文章 摘要内容 文章的内容 HOG特征表示 可变形部件建模 可变形部件匹配 建立目标函数 求解目标函数 数据发掘利用难样本 训练流程 后处理 实验结果 讨论 相关文章 Object Detection with Discriminatively Trained Part Based Models. To appear in PAMI. 会议文章的扩展，(1)SVM求解改进(2)mixtured models(3)特征的改进(4)后处理 Cascade Object Detection with Deformable Part Models. In CVPR,2010. 将本文的检测框架中速度的瓶颈部分改成层级结构。 Discriminative models for multi-class object. In ICCV, 2009. 是第三作者的工作，类似方法用于从同一图像中同时检测多类物体。 Distance Transforms of Sampled Functions. In TR, 2004. 本文作者早期的在动态规划方面的工作，用于快速的求得一个优化问题，在本文中用到了部件相对位置的优化，但是不具体介绍算法。 提纲 作者信息 相关文章 摘要内容 文章的内容 可变形部件建模 可变形部件匹配 建立目标函数 求解目标函数 数据发掘利用难样本 训练流程 HOG特征表示 后处理 实验结果 讨论 摘要内容(1/2) 1. This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007 challenge in ten out of twenty categories. . 2. The system relies heavily on deformable parts. While deformable part models have become quite popular, their value had not been demonstrated on difficult benchmarks such as the PASCAL challenge. Our system also relies heavily on new methods for