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Occlusion cues for image scene layering
- Source :
- Computer Vision and Image Understanding. 117:42-55
- Publication Year :
- 2013
- Publisher :
- Elsevier BV, 2013.
-
Abstract
- To bring computer vision closer to human vision, we attempt to enable computer to understand the occlusion relationship in an image. In this paper, we propose five low dimensional region-based occlusion cues inspired by the human perception of occlusion. These cues are semantic cue, position cue, compactness cue, shared boundary cue and junction cue. We apply these cues to predict the region-wise occlusion relationship in an image and infer the layer sequence of the image scene. A preference function, trained with samples consisting of these cues, is defined to predict the occlusion relationship in an image. Then we put all the occlusion predictions into the layering algorithm to infer the layer sequence of the image scene. The experiments on rural, artificial and outdoor scene datasets show the effectiveness of our method for occlusion relationship prediction and image scene layering.
- Subjects :
- genetic structures
business.industry
Computer science
media_common.quotation_subject
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Preference function
Image (mathematics)
Perception
Signal Processing
Occlusion
Computer vision
Computer Vision and Pattern Recognition
Artificial intelligence
Layering
business
Software
ComputingMethodologies_COMPUTERGRAPHICS
media_common
Subjects
Details
- ISSN :
- 10773142
- Volume :
- 117
- Database :
- OpenAIRE
- Journal :
- Computer Vision and Image Understanding
- Accession number :
- edsair.doi...........73e3673cd253d9d1033975c1bd11ba45