TY - GEN
T1 - An Efficient Dense Depth Map Estimation Algorithm Using Direct Stereo Matching for Ultra-Wide-Angle Images
AU - Gui, Xiuxiu
AU - Zhang, Xinyu
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - We present an efficient dense depth map estimation algorithm using patch-based direct stereo matching for ultra-wide-angle images. Our algorithm takes account of the fact that the neighboring pixels inside a local patch are likely to lie on the same plane. Our algorithm propagates the “good” initial guesses to the neighboring pixels by spatial propagation, followed by a random refinement process. Therefore, this allows finding precise depth value for each point in an infinite space using a random search strategy. Our algorithm can be used to perform 3D reconstruction using the dense depth maps directly generated from ultra-wide-angle images, especially from stereo camera pairs.
AB - We present an efficient dense depth map estimation algorithm using patch-based direct stereo matching for ultra-wide-angle images. Our algorithm takes account of the fact that the neighboring pixels inside a local patch are likely to lie on the same plane. Our algorithm propagates the “good” initial guesses to the neighboring pixels by spatial propagation, followed by a random refinement process. Therefore, this allows finding precise depth value for each point in an infinite space using a random search strategy. Our algorithm can be used to perform 3D reconstruction using the dense depth maps directly generated from ultra-wide-angle images, especially from stereo camera pairs.
KW - Depth map
KW - Patch-based stereo matching
KW - Ultra-wide-angle camera
UR - https://www.scopus.com/pages/publications/85148032667
U2 - 10.1007/978-3-031-23473-6_10
DO - 10.1007/978-3-031-23473-6_10
M3 - 会议稿件
AN - SCOPUS:85148032667
SN - 9783031234729
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 117
EP - 128
BT - Advances in Computer Graphics - 39th Computer Graphics International Conference, CGI 2022, Proceedings
A2 - Magnenat-Thalmann, Nadia
A2 - Zhang, Jian
A2 - Kim, Jinman
A2 - Papagiannakis, George
A2 - Sheng, Bin
A2 - Thalmann, Daniel
A2 - Gavrilova, Marina
PB - Springer Science and Business Media Deutschland GmbH
T2 - 39th Computer Graphics International Conference on Advances in Computer Graphics, CGI 2022
Y2 - 12 September 2022 through 16 September 2022
ER -