Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Efficient Graph-Based Image Segmentation
International Journal of Computer Vision
ACM SIGGRAPH 2005 Papers
Geometric Context from a Single Image
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Make3D: Learning 3D Scene Structure from a Single Still Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
Make3D: depth perception from a single still image
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Stages as Models of Scene Geometry
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time estimation of 3D scene geometry from a single image
Pattern Recognition
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Content Based Image Retrieval (CBIR) has been an active research field for a long time. Existing CBIR approaches are mostly based on low- to middle-level visual cues such as color or color histograms and possibly semantic relations of image regions, etc. In many applications, it may be of interest to retrieve images of similar geometrical configurations such as all images of a hallway-like view. In this paper we present our work on addressing such a task that seemingly requires 3D reconstruction from a single image. Our approach avoids explicit 3D reconstruction, which remains to be a challenge, through coding the potential relationship between the 3D structure of an image and its low-level features via a grid-based representation. We experimented with a data set of several thousands of images and obtained promising results.