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20150122-03 禹之鼎|张正武:Highway Border Detection & Functional Data

2015-2-26 15:30| 发布者: zhenghaiyong| 查看: 2730| 评论: 0|来自: VALSE

摘要: 报告嘉宾1:禹之鼎(CMU,Valse QQ群管理员)主持人:彭玺(A*Star)报告时间:2015年1月22日晚21:00(北京时间)报告题目:Structured Hough Voting for Vision-based Highway Border DetectionStructured_Hough_Vo ...
  • 报告嘉宾1:禹之鼎(CMU,Valse QQ群管理员)
  • 主持人:彭玺(A*Star)
  • 报告时间:2015年1月22日晚21:00(北京时间)
  • 报告题目:Structured Hough Voting for Vision-based Highway Border Detection
  • 文章信息:Zhiding Yu, Wende Zhang, B. V. K. Vijaya Kumar and Dan Levi, Structured Hough Voting for Vision-based Highway Border Detection, IEEE Winter Conference on Applications of Computer Vision (WACV), 2015. (Best Paper Award) [Paper] [Demo]
  • 报告摘要:We propose a vision-based highway border detection algorithm using structured Hough voting. Our approach takes advantage of the geometric relationship between highway road borders and highway lane markings. It uses a strategy where a number of trained road border and lane marking detectors are triggered, followed by Hough voting to generate corresponding detection of the border and lane marking. Since the initially triggered detectors usually result in large number of positives, conventional frame-wise Hough voting is not able to always generate robust border and lane marking results. Therefore, we formulate this problem as a joint detection-and-tracking problem under the structured Hough voting model, where tracking refers to exploiting inter-frame structural information to stabilize the detection results. Both qualitative and quantitative evaluations show the superiority of the proposed structured Hough voting model over a number of baseline methods.
  • 报告人简介:禹之鼎现在是卡内基梅隆大学电气与计算机工程系三年级博士生(博士导师Vijayakumar Bhagavatula)。2005年至2008年本科期间就读于华南理工大学电子类联合班。2009年和2012年分别获得香港科技大学电子及计算机系M.Sc.与M.Phil.学位(硕士导师Oscar Au)。硕士和博士期间曾分别在中科院深圳先进技术研究院多媒体实验室以及Adobe Research实习。于2010年和2012年两次获得HKTIIT Post-Graduate Excellence Scholarship;2014年和2015年分别获得ISCSLP Best Student Paper Award (Co-Author) 以及WACV Best Paper Award。在包括CVPR,ACM-MM,WACV,ICME,ICIP,Pattern Recognition等会议和期刊上发表文章20余篇。具体请详见

  1. Zhengwu Zhang, Eric Klassen, Anuj Srivastava, Gaussian Blurring-invariant Comparison of Signals and Images. IEEE Transactions on Image Processing, Aug. 2013, Vol 22, No. 8. [PDF]
  2. Zhengwu Zhang, Debdeep Pati, Anuj Srivastava, Bayesian Clustering of Shapes of Curves Using Dirichlet-Wishart Prior. Journal of Statistical Planning and Inference, 2014. (Revision submitted) [PDF]
  • 报告摘要:In this talk, I will introduce a comprehensive framework for a joint registration and analysis of functional data. The term functional data is used here very generally as it encompasses a variety of situations including registration of real-valued functions, Euclidean curves, and trajectories on nonlinear manifolds. This framework uses the Fisher-Rao Riemannian metric to derive a proper distance on the quotient space of functions modulo the time-warping group. A convenient square-root velocity function (SRVF) representation transforms the Fisher-Rao metric into the standard L2 metric, simplifying the computations. This distance is then used to define a Karcher mean template and warp the individual functions to align them with the Karcher mean template. The advantages of this framework are demonstrated using both simulated and real data from different application domains.
  • 报告人简介:张正武现在是佛罗里达州立大学(FSU) 统计系五年级博士(博士导师: Anuj Srivastava)。2005年至2008年本科期间就读于华南理工大学电子类联合班。2010年于中山大学信息科学与技术学院获得硕士学位。 在包括TIP,ICCV,ACM Multimedia,JSPI,Annuals of Applied Statistics,Scandinavian Journal of Statistics等会议和杂志有已发表或再审论文。 详细信息请参见:


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