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Depth Extraction from Videos Using Geometric Context and Occlusion Boundaries
[article]
2015
arXiv
pre-print
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We present an algorithm to estimate depth in dynamic video scenes. We propose to learn and infer depth in videos from appearance, motion, occlusion boundaries, and geometric context of the scene. ...
Using our method, depth can be estimated from unconstrained videos with no requirement of camera pose estimation, and with significant background/foreground motions. ...
Motion features are also useful for extracting geometric context in videos and occlusion boundaries detection. Our approach for depth estimation can also be applied to images. ...
arXiv:1510.07317v1
fatcat:ux2awhqrbver5nkibf4xuxf26u
Depth Extraction from Videos Using Geometric Context and Occlusion Boundaries
2014
Proceedings of the British Machine Vision Conference 2014
unpublished
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We present an algorithm to estimate depth in dynamic video scenes. We propose to learn and infer depth in videos from appearance, motion, occlusion boundaries, and geometric context of the scene. ...
Using our method, depth can be estimated from unconstrained videos with no requirement of camera pose estimation, and with significant background/foreground motions. ...
It should be noted that our algorithm depends on occlusion boundary detection and geometric context (for which motion based features are important and is not optimized to extract depth from single images ...
doi:10.5244/c.28.10
fatcat:hiho7srodvdy3egfdcmdb57vim
Finding Temporally Consistent Occlusion Boundaries in Videos Using Geometric Context
2015
2015 IEEE Winter Conference on Applications of Computer Vision
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2015 pre-print arXiv:1510.07323v1 fatcat:yiijd6qv7zeapm3ela5wzv2bi4
We first estimate the probability of an spatio-temporal edge being an occlusion boundary by using appearance, flow, and geometric features. ...
This dataset is used to evaluate temporal occlusion boundaries and provides a much needed baseline for future studies. ...
Some videos were recorded while walking, some while driving, and others were downloaded from YouTube. We also included few videos from recently released video geometric context dataset from Raza et al ...
doi:10.1109/wacv.2015.141
dblp:conf/wacv/RazaHEGA15
fatcat:ohwzi7pifzdufcxk534awvh6gm
Automatic 3D Indoor Scene Modeling from Single Panorama
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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Using sampled perspective subviews, we extract geometric cues (lines, vanishing points, orientation map, and surface normals) and semantic cues (saliency and object detection information). ...
We describe a system that automatically extracts 3D geometry of an indoor scene from a single 2D panorama. ...
Geometric context and orientation map generation. We follow the same strategy in [32] to extract the geometric context (GC) [9] and orientation map (OM) [15] , respectively. ...
doi:10.1109/cvpr.2018.00413
dblp:conf/cvpr/YangJLKY18
fatcat:ipbbt5ucundb3efpzr7zitgjzi
Object-Based 2D-to-3D Video Conversion for Effective Stereoscopic Content Generation in 3D-TV Applications
2011
IEEE transactions on broadcasting
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Although stereoscopic video can be generated from monoscopic sequences using depth measurements extracted from cues like focus blur, motion and size, the quality of the resulting video may be poor as such ...
using improved region-growing from masks of determined depth layers, and iii) a hybrid depth estimation scheme using content-based matching (inside a small library of true stereo image pairs) and depth-ordinal ...
Tam for providing some of the test data and carefully revising our paper as well as Dr C. Watkins and Dr. G. Gonzalezcastro of Bradford University for proofreading this paper. ...
doi:10.1109/tbc.2011.2131030
fatcat:cg62lceagvgmzif4obd4ei6q54
Behind the Scenes: What Moving Targets Reveal about Static Scene Geometry
2013
2013 IEEE International Conference on Computer Vision Workshops
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Finally, we show how the proposed geometric cues can be used to infer an ordinal depth map and demonstrate its use in compositing with correct occlusion handling. ...
Figure 1: Scene geometry from moving targets: (left) video frame; (right) occluding (green), occluded (blue) and supporting (red) segments, and occlusion boundary (black). ...
The algorithm takes video from a single static camera as input, and determines the likelihood of a static occlusion boundary and a floor region at each pixel. ...
doi:10.1109/iccvw.2013.76
dblp:conf/iccvw/TaylorM13
fatcat:kpoanttxlvglvjes2woqrikqku
Occlusion Boundary Detection via Deep Exploration of Context
2016
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
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In this paper, we improve occlusion boundary detection via enhanced exploration of contextual information (e.g., local structural boundary patterns, observations from surrounding regions, and temporal ...
context), and in doing so develop a novel approach based on convolutional neural networks (CNNs) and conditional random fields (CRFs). ...
Acknowledgment This work is partly supported by Australian Research Council Projects (DP-140102164, FT-130101457, LE140100061) and CNRS INS2I-JCJC-INVISANA. ...
doi:10.1109/cvpr.2016.33
dblp:conf/cvpr/FuWTB16
fatcat:fvbcsfdmyrbu3m5pa5yaiwe7ea
Range-Sample Depth Feature for Action Recognition
2014
2014 IEEE Conference on Computer Vision and Pattern Recognition
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We propose binary range-sample feature in depth. It is based on τ tests and achieves reasonable invariance with respect to possible change in scale, viewpoint, and background. ...
It is robust to occlusion and data corruption as well. The descriptor works in a high speed thanks to its binary property. ...
Unlike these methods, we exploit more 3D geometric relationship (e.g., occlusion and layers) inherent in the available depth. ...
doi:10.1109/cvpr.2014.104
dblp:conf/cvpr/LuJT14
fatcat:ligzuzmjfndz5c3o6lkxsuxvsq
Accurate Human Body Reconstruction for Volumetric Video
[article]
2022
arXiv
pre-print
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Other Versions
2021
2021 International Conference on 3D Immersion (IC3D)
unpublished
doi:10.1109/ic3d53758.2021.9687256 fatcat:s4jbmqdc3jbhdf26xfbsyvqihq
doi:10.1109/ic3d53758.2021.9687256 fatcat:s4jbmqdc3jbhdf26xfbsyvqihq
While current volumetric video approaches estimate depth maps using traditional stereo matching techniques, we introduce and optimize deep learning-based multi-view stereo networks for depth map estimation ...
in the context of professional volumetric video reconstruction. ...
Berlin in the context of the KIVI project and the European Union's Horizon 2020 research and innovation program under Grant Agreement 952147 (Invictus). ...
arXiv:2202.13118v1
fatcat:nz53fexmkfbifejr3f6fj2ke2e
Occlusion-Aware Depth Estimation with Adaptive Normal Constraints
[article]
2020
arXiv
pre-print
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In order to further improve the depth estimation accuracy, we introduce a new occlusion-aware strategy that aggregates initial depth predictions from multiple adjacent views into one final depth map and ...
We present a new learning-based method for multi-frame depth estimation from a color video, which is a fundamental problem in scene understanding, robot navigation or handheld 3D reconstruction. ...
In Fig. 3 , the point cloud converted from estimated depth becomes cleaner and has sharp boundaries by applying the occlusion probability map to the multi-view depth integration process. ...
arXiv:2004.00845v2
fatcat:bfkqx2sjk5annhj276tpozdxjq
BRANCH:Bifurcation Recognition for Airway Navigation based on struCtural cHaracteristics
[chapter]
2017
Lecture Notes in Computer Science
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Salient regions are detected on the depth maps of video images and CT virtual projections to extract anatomically meaningful areas that represent airway bifurcations. ...
The bronchoscopic camera is localised in the airways by minimising the cost of matching the region features in video images to the pre-computed CT depth maps considering both the shape and temporal information ...
Giannarou is grateful for the support from the Royal Society (UF140290). ...
doi:10.1007/978-3-319-66185-8_21
fatcat:4etfthcibrd6hm3x5ievkdiqly
Occlusion Boundary: A Formal Definition & Its Detection via Deep Exploration of Context
2020
IEEE Transactions on Pattern Analysis and Machine Intelligence
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., local structural boundary patterns, observations from surrounding regions, and temporal context) with deep models and conditional random fields. ...
However, there is no formal definition of occlusion boundaries in the literature, and state-of-the-art occlusion boundary detection is still suboptimal. ...
[9] demonstrate the importance of 2D perceptual cues and 3D surface and depth cues for occlusion boundary detection, and compute these geometric contexts to reason about occlusions within their CRF ...
doi:10.1109/tpami.2020.3039478
pmid:33211655
fatcat:wxhvxjnbibcl7futyvt7lqelsi
Interactive images
2012
ACM Transactions on Graphics
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Here, we replace furniture in one image using candidates from other images, while automatically conforming to the non-local relations extracted from the original scene, e.g., the sofas have the same heights ...
Abstract Images are static and lack important depth information about the underlying 3D scenes. ...
Alhalawani for the video voiceover. ...
doi:10.1145/2185520.2185595
fatcat:dup3uvugarexllurdbs4prbeai
Interactive images
2012
ACM Transactions on Graphics
Preserved Fulltext
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Here, we replace furniture in one image using candidates from other images, while automatically conforming to the non-local relations extracted from the original scene, e.g., the sofas have the same heights ...
Abstract Images are static and lack important depth information about the underlying 3D scenes. ...
Alhalawani for the video voiceover. ...
doi:10.1145/2185520.2335450
fatcat:wlhnczp7i5b6la4b7jsaegkms4
Recovering Occlusion Boundaries from an Image
2010
International Journal of Computer Vision
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In this paper, we propose an algorithm to recover the occlusion boundaries and depth ordering of free-standing structures in the scene. ...
Our experiments on the Geometric Context dataset validate our choices for features, our iterative refinement of classifiers, and our CRF model. ...
This material is based upon work supported by the NSF under award IIS-0904209 (DH) and CAREER award IIS-0546547 (AE), as well as a Microsoft Graduate Fellowship (DH). ...
doi:10.1007/s11263-010-0400-4
fatcat:wjz5ewjkebfqlotitd6btoaotm
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