This demonstrator explores the applicability of depth estimation based on stereo video with extremely low resolution, i.e., 3030 pixels. To handle this resolution, this paper proposes a disparity estimation technique, composed of local correlation-based matching of two low-resolution stereo images followed by segmentation-driven post-processing. The demonstrator includes a setup where a stereo visual sensor is connected to a laptop computer, running the proposed depth estimation method in real-time and displaying the resulting disparity maps. In addition, an interface is available to give the user control over the proposed algorithm parameters. To illustrate the superior performance, the results of proposed method can be readily compared to disparity maps generated using a typical global correlation-based depth estimation algorithm.
Hanca, J, Verbist, F, Deligiannis, N, Kleihorst, R & Munteanu, A 2013, Demo: Depth estimation for 1K-pixel stereo visual sensors. in ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC2013. IEEE, Distributed Smart Cameras (ICDSC), 2013 Seventh International Conference on, Palm Springs, United States, 29/10/13.
Hanca, J., Verbist, F., Deligiannis, N., Kleihorst, R., & Munteanu, A. (2013). Demo: Depth estimation for 1K-pixel stereo visual sensors. In ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC2013 IEEE.
@inproceedings{af6b160da4fb45408d59f5204cb59ff1,
title = "Demo: Depth estimation for 1K-pixel stereo visual sensors",
abstract = "This demonstrator explores the applicability of depth estimation based on stereo video with extremely low resolution, i.e., 3030 pixels. To handle this resolution, this paper proposes a disparity estimation technique, composed of local correlation-based matching of two low-resolution stereo images followed by segmentation-driven post-processing. The demonstrator includes a setup where a stereo visual sensor is connected to a laptop computer, running the proposed depth estimation method in real-time and displaying the resulting disparity maps. In addition, an interface is available to give the user control over the proposed algorithm parameters. To illustrate the superior performance, the results of proposed method can be readily compared to disparity maps generated using a typical global correlation-based depth estimation algorithm.",
keywords = "visual sensors, depth map estimation, disparity",
author = "Jan Hanca and Frederik Verbist and Nikolaos Deligiannis and Richard Kleihorst and Adrian Munteanu",
year = "2013",
month = oct,
day = "31",
language = "English",
isbn = "978-1-4799-2166-9",
booktitle = "ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC2013",
publisher = "IEEE",
note = "Distributed Smart Cameras (ICDSC), 2013 Seventh International Conference on ; Conference date: 29-10-2013 Through 01-11-2013",
}