Computer Science ›› 2018, Vol. 45 ›› Issue (12): 235-242.doi: 10.11896/j.issn.1002-137X.2018.12.039

• Graphics, Image & Pattern Recognition • Previous Articles     Next Articles

Surface Labeling Method Based on Feed-forward Context and Shape Priors

GUO Yan-fei1, LIU Hong-zhe1, YUAN Jia-zheng1,2, WANG Xue-jiao1   

  1. (Beijing Key Laboratory of Information Service Engineering,Beijing Union University,Beijing 100101,China)1
    (Beijing Open University,Beijing 100081,China)2
  • Received:2017-11-10 Online:2018-12-15 Published:2019-02-25

Abstract: Aiming at the problem that the scene semantics cannot be understood caused by mutual occlusion,this paper proposed a method based on feed-forward context and shape priors to semantically label the foreground region and the occluded background area.Firstly,the original image is divided into super pixels,and the feature of pixel is extracted.The accelerated decision tree method is used to mark the foreground and the target model is detected by the improved multi-scale deformable component model method.Then,the visible object information is combined with the feed-forward context prediction to infer the occluded portions of background region.Next,the prior knowledge of shape for each label is provided based on polygons which match the current label confidence.Finally,the pixel prediction is combined with the visual plane prediction and the polygon knowledge to form a complete scene labeling image.Compared with the exis-ting method,this method can get more consistent results with the street scene,and can perform better labeling effect when the sidewalk is close to the road.

Key words: Scene understanding, Surface labeling, Multi-scale deformable component model, Feed-forward context, Shape priors

CLC Number: 

  • TP391
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