The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Depth from Combining Defocus and Correspondence Using Light-Field Cameras
Abstract
Light-field cameras have recently become available to the consumer market. An array of micro-lenses captures enough information that one can refocus images after acquisition, as well as shift one's viewpoint within the sub-apertures of the main lens, effectively obtaining multiple views. Thus, depth cues from both defocus and correspondence are available simultaneously in a single capture. Previously, defocus could be achieved only through multiple image exposures focused at different depths, while correspondence cues needed multiple exposures at different viewpoints or multiple cameras, moreover, both cues could not easily be obtained together. In this paper, we present a novel simple and principled algorithm that computes dense depth estimation by combining both defocus and correspondence depth cues. We analyze the x-u 2D epipolar image (EPI), where by convention we assume the spatial x coordinate is horizontal and the angular u coordinate is vertical (our final algorithm uses the full 4D EPI). We show that defocus depth cues are obtained by computing the horizontal (spatial) variance after vertical (angular) integration, and correspondence depth cues by computing the vertical (angular) variance. We then show how to combine the two cues into a high quality depth map, suitable for computer vision applications such as matting, full control of depth-of-field, and surface reconstruction.
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Cites
A Database and Evaluation Methodology for Optical Flow
Baker, S., Scharstein, D., Lewis, J. P., Roth, S., Black, M. J., & Szeliski, R. (2011) · International Journal of Computer Vision · doi:10.1007/s11263-010-0390-2 · Cited by 2,205 · cited 1×
“is one of the top performers on the Middlebury’s dataset [2].”
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Cited by
Light Field Image Processing: An Overview
Wu, G., Masia, B., Jarabo, A., Zhang, Y., Wang, L., Dai, Q., Chai, T., & Liu, Y. (2017) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2017.2747126 · Cited by 586
Adaptive EPI-Matching Cost for Light Field Disparity Estimation
Wang, T., Sheng, H., Chen, R., Cong, R., Zhao, M., & Cui, Z. (2024) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2024.3488147 · Cited by 348
Shin, C., Jeon, H.-G., Yoon, Y., Kweon, I. S., & Kim, S. J. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00499 · Cited by 319
Lu, H., Li, Y., Uemura, T., Kim, H., & Serikawa, S. (2018) · Future Generation Computer Systems · doi:10.1016/j.future.2018.01.001 · Cited by 290
Metadata
- Authors
- Tao, M. W., Hadap, S., Malik, J., & Ramamoorthi, R.
- Venue
- 2013 IEEE International Conference on Computer Vision
- Publisher
- IEEE
- Published
- 2013-12
- Pages
- 673-680
- OpenAlex
- W2149694199
- Cited by
- 506
- References
- 1
- FWCI
- 20.69
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Tao, M. W., Hadap, S., Malik, J., & Ramamoorthi, R. (2013). Depth from Combining Defocus and Correspondence Using Light-Field Cameras. 2013 IEEE International Conference on Computer Vision. https://doi.org/10.1109/iccv.2013.89
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