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Blocks World Revisited: Image Understanding Using Qualitative Geometry and Mechanics
Open accessAbstract
Since most current scene understanding approaches operate either on the 2D image or using a surface-based representation, they do not allow reasoning about the physical constraints within the 3D scene. Inspired by the "Blocks World" work in the 1960's, we present a qualitative physical representation of an outdoor scene where objects have volume and mass, and relationships describe 3D structure and mechanical configurations. Our representation allows us to apply powerful global geometric constraints between 3D volumes as well as the laws of statics in a qualitative manner. We also present a novel iterative "interpretation-by-synthesis" approach where, starting from an empty ground plane, we progressively "build up" a physically-plausible 3D interpretation of the image. For surface layout estimation, our method demonstrates an improvement in performance over the state-of-the-art [9]. But more importantly, our approach automatically generates 3D parse graphs which describe qualitative geometric and mechanical properties of objects and relationships between objects within an image.
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Cites
Recovering Occlusion Boundaries from a Single Image
Hoiem, D., Stein, A. N., Efros, A. A., & Hebert, M. (2007) · 2007 IEEE 11th International Conference on Computer Vision · doi:10.1109/iccv.2007.4408985 · Cited by 206
Self-citation
Cited by
Indoor segmentation and support inference from rgbd images
Silberman, N., Hoiem, D., Kohli, P., & Fergus, R. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33715-4_54 · Cited by 5,760
Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields
Liu, F., Shen, C., Lin, G., & Reid, I. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2505283 · Cited by 1,240
Deep convolutional neural fields for depth estimation from a single image
Liu, F., Shen, C., & Lin, G. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2015.7299152 · Cited by 892
Seeing 3D Chairs: Exemplar Part-Based 2D-3D Alignment Using a Large Dataset of CAD Models
Aubry, M., Maturana, D., Efros, A. A., Russell, B. C., & Sivic, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.487 · Cited by 473
Self-citationDiscrete-Continuous Depth Estimation from a Single Image
Liu, M., Salzmann, M., & He, X. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.97 · Cited by 381
Metadata
- Authors
- Gupta, A., Efros, A. A., & Hebert, M.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2010
- Pages
- 482-496
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1486646730
- Cited by
- 308
- References
- 1
- FWCI
- 24.74
- Type
- conference paper
- Language
- en
- Open access
- green
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- Gupta, A., Efros, A. A., & Hebert, M. (2010). Blocks World Revisited: Image Understanding Using Qualitative Geometry and Mechanics. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-642-15561-1_35
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