Integrating Context and Occlusion for Car Detection by Hierarchical And-Or Model

We present a reconfigurable hierarchical And-Or model to integrate context and occlusion for car detection in the wild. The model structure is learned by mining context and viewpoint-occlusion patterns at three levels: a) N-car layouts, b) single car and c)
car parts. Our model is a directed acyclic graph (DAG) where dynamic programming (DP) algorithm can be used in inference. The model parameters are learned by weak-label Structural SVM. Experimental results show that our model is effective in modelling context
and occlusion information in complex situations, and obtains better performance over state-of-the-art car detection methods.

这里附上自己调通的代码，需要的各种依赖库自己去下载和配置。

代码下载地址：http://download.csdn.net/download/gone_huilin/9687167

参考：http://www.stat.ucla.edu/~boli/projects/context_occlusion/context_occlusion.html