Image classification using latent spatial pyramid matching.

详细信息   

• 作者：Yu ; Pengfei.
• 学历：Master
• 年：2011
• 关键词：image classification ; latent spatial pyramid matchi
• 毕业院校：Simon Fraser University
• Department：Computing Science.
• ISBN：9780499233882
• CBH：MS23388
• Country：Canada
• 语种：English
• FileSize：8349216
• Pages：79

文摘

We present work on image classification in this thesis. Image classification is a classical task in computer vision,whose goal is to determine whether or not any instances of a particular object class appear in a given image. There are three major pieces of work. First,we proposed a novel Latent Spatial Pyramid Matching L-SPM) feature representation inspired by the state-of-art Spatial Pyramid Matching SPM) [29] feature representation. L-SPM allows the cells of the pyramid to move within reasonable regions instead of a predefined rigid partition. Second,we utilize Efficient Subwindow Search [28] based on a branch-and-bound algorithm to select the position and size for the latent cells. Third,we implement the Latent SVM framework proposed by Felzenszwalb et al. [21] to solve the non-convex optimization problem. Results are reported for image classification on the Pascal VOC 2007 data set.