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View synthesis by trinocular edge matching and transfer
2000
Image and Vision Computing
Preserved Fulltext
This paper presents a novel automatic method for view synthesis (or image transfer) from a triplet of uncalibrated images based on trinocular edge matching followed by transfer by interpolation, occlusion ...
detection and correction and finally rendering. ...
Additionally, for completeness of the synthesised images, extra edge
Creating virtual views A virtual view is created by first transferring edges into a virtual "sketch" and then by colouring raster ...
doi:10.1016/s0262-8856(99)00078-5
fatcat:n3jly2mgorhgjg5urmwjblc5ju
View Synthesis by Trinocular Edge Matching and Transfer
1998
Procedings of the British Machine Vision Conference 1998
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This paper presents a novel automatic method for view synthesis (or image transfer) from a triplet of uncalibrated images based on trinocular edge matching followed by transfer by interpolation, occlusion ...
detection and correction and finally rendering. ...
Additionally, for completeness of the synthesised images, extra edge
Creating virtual views A virtual view is created by first transferring edges into a virtual "sketch" and then by colouring raster ...
doi:10.5244/c.12.77
dblp:conf/bmvc/PollardPHL98
fatcat:lorcefw6kzcb7pcqdrcpa46awa
View synthesis by trinocular edge matching and transfer
Proceedings Fourth IEEE Workshop on Applications of Computer Vision. WACV'98 (Cat. No.98EX201)
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This paper presents a novel automatic method for view synthesis (or image transfer) from a triplet of uncalibrated images based on trinocular edge matching followed by transfer by interpolation, occlusion ...
detection and correction and finally rendering. ...
Additionally, for completeness of the synthesised images, extra edge
Creating virtual views A virtual view is created by first transferring edges into a virtual "sketch" and then by colouring raster ...
doi:10.1109/acv.1998.732875
dblp:conf/wacv/PollardPHL98
fatcat:r6n6jdlzlzhejecy4ku5oeccjy
Learning monocular depth estimation with unsupervised trinocular assumptions
[article]
2018
arXiv
pre-print
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Therefore, in this paper, we tackle these issues by moving to a trinocular domain for training. ...
This strategy allows obtaining depth maps not affected by typical stereo artifacts. ...
[25] formulated the monocular depth estimation problem as a view synthesis procedure followed by a deep stereo matching approach. Kumar et al. ...
arXiv:1808.01606v1
fatcat:lfn2nad44vexpcrkyp5wdlcn3y
Inverse tensor transfer with applications to novel view synthesis and multi-baseline stereo
2006
Signal processing. Image communication
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A new tensor transfer-based NVS (novel view synthesis) method is proposed in this paper. ...
By using this inverse transfer idea, we are able to handle non-ideally configured multi-baseline stereo in a natural and efficient way. ...
The authors wish to thank editors and anonymous reviewers for their invaluable comments. ...
doi:10.1016/j.image.2006.07.004
fatcat:va65oa3kbffavdaxyqictqdq4e
Super-resolution of a 3-dimensional scene from novel viewpoints
2012
2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)
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The proposed robust inverse tensor transfer algorithm for novel view synthesis achieves significant robustness and quality improvements compared to existing methods by introducing a novel multi-stage approach ...
inverse tensor transfer for novel view synthesis, culminating in method for multi-view super-resolution which demonstrates that it is indeed possible to extend superresolution concepts from two dimensions ...
reference view can have on a view synthesised by tensor transfer. ...
doi:10.1109/icarcv.2012.6485347
dblp:conf/icarcv/NelsonBN12
fatcat:wfakbldhzfhl3jlkcwsuu7v34m
Deconstructing Self-Supervised Monocular Reconstruction: The Design Decisions that Matter
[article]
2022
arXiv
pre-print
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We re-implement, validate and re-evaluate 16 state-of-the-art contributions and introduce a new dataset (SYNS-Patches) containing dense outdoor depth maps in a variety of both natural and urban scenes. ...
It is likely that many papers were not only optimized for particular datasets, but also for errors in the data and evaluation criteria. ...
This is achieved by applying the view synthesis module to the disparities, as opposed to the images. ...
arXiv:2208.01489v1
fatcat:4bxoe7lryjgmvpjvisd4l4q6cy
Front Matter: Volume 1395
1990
Close-Range Photogrammetry Meets Machine Vision
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Sun, SESSION B9 ALGORITHMIC ASPECTS IN IMAGE ANALYSIS III
Straight-edge extraction and matching
Y. Liu, T. S. ...
Sun, Wuhan Technical Univ. of Surveying and Mapping (China)
595
602
605
SESSION B9 ALGORITHMIC ASPECTS IN IMAGE ANALYSIS III
Straight -edge extraction and matching
Y. Liu, T. S. ...
doi:10.1117/12.2294402
fatcat:tf44q76e6jeolp54b6fhr7lxoy
A Real-Time Model-Based Human Motion Tracking and Analysis for Human-Computer Interface Systems
2004
EURASIP Journal on Advances in Signal Processing
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The motion parameters are estimated by pattern matching between the extracted human silhouette and the human model. ...
This method tracks and analyzes the human motion from two orthogonal views without using any markers. ...
The abstract levels for comparing image data and synthesis data can be edges, silhouettes, contours, sticks, joints, blobs, texture, motion, and so forth. ...
doi:10.1155/s1110865704401206
fatcat:exdtoz6nszen7lbwmllaiq6uei
Deep Learning for Omnidirectional Vision: A Survey and New Perspectives
[article]
2022
arXiv
pre-print
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(iv) An insightful discussion of the challenges and open problems by highlighting the potential research directions to trigger more research in the community. ...
Omnidirectional image (ODI) data is captured with a 360x180 field-of-view, which is much wider than the pinhole cameras and contains richer spatial information than the conventional planar images. ...
Cross-view Synthesis and Geo-localization Insight: Cross-view synthesis aims to synthesize ground-view ODIs from the satellite-view images while geo-localization aims to match the ground-view ODIs and ...
arXiv:2205.10468v2
fatcat:73fks33oafa6zgxliccydvdbeq
Monocular Depth Estimation Based On Deep Learning: An Overview
[article]
2020
arXiv
pre-print
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Traditional depth estimation methods, like structure from motion and stereo vision matching, are built on feature correspondences of multiple viewpoints. ...
Meanwhile, dense depth maps are estimated from single images by deep neural networks in an end-to-end manner. ...
Features from different viewpoints are synthesised by performing stereo matching, thereby achieving outstanding performance. ...
arXiv:2003.06620v1
fatcat:l5ei3ognova6xkyppflef5nqsq
On the Synergies between Machine Learning and Binocular Stereo for Depth Estimation from Images: a Survey
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2004.08566v1 fatcat:hnoaq6ov5zgd7kye6t5g2534iy
Stereo matching is one of the longest-standing problems in computer vision with close to 40 years of studies and research. ...
Recently, the rise of machine learning and the rapid proliferation of deep learning enhanced stereo matching with new exciting trends and applications unthinkable until a few years ago. ...
To overcome this limitation, three main categories of techniques aiming to bridge the gap between synthetic and real domains have been proposed: i) image synthesis and domain transfer, ii) self-supervised ...
arXiv:2004.08566v2
fatcat:wcwfgzibo5evbkun3atpsz6kwm
Unsupervised Learning of Monocular Depth Estimation with Bundle Adjustment, Super-Resolution and Clip Loss
[article]
2018
arXiv
pre-print
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In bundle adjustment, depths and poses of an image sequence are jointly optimized, which increases the baseline by establishing the relationship between farther frames. ...
We present a novel unsupervised learning framework for single view depth estimation using monocular videos. ...
Similarly, our algorithm jointly optimizes depths and camera poses by using photometric consistency loss and cross-sequence geometric consistency loss. Arcs represent view synthesis. ...
arXiv:1812.03368v1
fatcat:462ptqvitjcmlmhig6im2hmmke
2020 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 30
2020
IEEE transactions on circuits and systems for video technology (Print)
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., TCSVT Jan. 2020 217-231 Hu, X., see Zhu, L., TCSVT Oct. 2020 3358-3371 Hu, Y., Lu, M., Xie, C., and Lu, X ...
., and Zeng, B., MUcast: Linear Uncoded Multiuser TCSVT Nov. 2020 4299-4308 Hu, R., see Chen, L., TCSVT Dec. 2020 4513-4525 Hu, R., see Wang, X., TCSVT Nov. 2020 4309-4320 Hu, X., see Zhang, X ...
Lin, C., TCSVT June 2020 1771-1784 A View Synthesis-Based 360° VR Caching System Over MEC-Enabled C-RAN. ...
doi:10.1109/tcsvt.2020.3043861
fatcat:s6z4wzp45vfflphgfcxh6x7npu
A secure and reliable next generation mobility
2009
Synthesiology English edition
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This wheelchair helps the rider to move safely indoors and outdoors and in space shared by pedestrians. ...
In chapter 3, we describe the selection of elemental technologies necessary for constructing the prototype, and chapter 4 presents the integration and the synthesis. ...
The screen is a touch panel, and the desired view can be displayed by touching the screen with a finger. ...
doi:10.5571/syntheng.2.107
fatcat:mm2u7fqbsfcqfmfyrpifdw5t6y
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