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Monocular 3D human pose estimation using sparse motion features
2009
2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops
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In this paper we demonstrate that the motion of a sparse set of tracked features can be used to extract 3D pose from a single viewpoint. ...
We use low-level part detectors consisting of 3D motion models, these describe probabilistically how well the observed motion of a tracked feature fits each model. ...
In this paper we describe a method to estimate 3D pose from a monocular camera using sparse and noisy motion features, we believe this to be the first attempt to do so and represents a significant step ...
doi:10.1109/iccvw.2009.5457586
dblp:conf/iccvw/DaubneyGC09
fatcat:chb5tz47bbhclkd2ijhpfd2ehy
MonoPerfCap: Human Performance Capture from Monocular Video
[article]
2018
arXiv
pre-print
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We tackle these challenges by a novel approach that employs sparse 2D and 3D human pose detections from a convolutional neural network using a batch-based pose estimation strategy. ...
We present the first marker-less approach for temporally coherent 3D performance capture of a human with general clothing from monocular video. ...
We tackle these challenges by a novel approach that employs sparse 2D and 3D human pose detections from a convolutional neural network using a batch-based pose estimation strategy. ...
arXiv:1708.02136v2
fatcat:toewmmbynnbppmxsop43d4xk3e
DnD: Dense Depth Estimation in Crowded Dynamic Indoor Scenes
[article]
2021
arXiv
pre-print
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Our network leverages RGB images and sparse depth maps generated from traditional 3D reconstruction methods to estimate dense depth maps. ...
We use two constraints to handle depth for non-rigidly moving people without tracking their motion explicitly. ...
We observe that a joint training framework of pose and depth from a monocular video is extremely difficult be-cause pose networks often fail to estimate proper camera ego-motion in complex and crowded ...
arXiv:2108.05615v1
fatcat:xqr72w6pnfhzzcfqp2wciqhsne
CamOdoCal: Automatic intrinsic and extrinsic calibration of a rig with multiple generic cameras and odometry
2013
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
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For robustness, vision applications tend to use wheel odometry as a strong prior for camera pose estimation, and in these cases, an accurate extrinsic calibration is required in addition to an accurate ...
The extrinsic calibration is unsupervised, uses natural features, and only requires the vehicle to be driven around for a short time. ...
Monocular VO We run monocular VO for each camera in order to obtain a set of camera motions together which is required for the subsequent step of computing an initial estimate of the extrinsics. ...
doi:10.1109/iros.2013.6696592
dblp:conf/iros/HengLP13
fatcat:crjxrd7cuzefblfqek3mr6np3e
PL-SVO: Semi-direct Monocular Visual Odometry by combining points and line segments
2016
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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Most approaches to visual odometry estimates the camera motion based on point features, consequently, their performance deteriorates in lowtextured scenes where it is difficult to find a reliable set of ...
This paper extends a popular semi-direct approach to monocular visual odometry known as SVO [1] to work with line segments, hence obtaining a more robust system capable of dealing with both textured and ...
using the 3D warping provided by the known 3D features. ...
doi:10.1109/iros.2016.7759620
dblp:conf/iros/Gomez-OjedaBJ16
fatcat:fiksk6rg6ndojoldf6jkio27aq
Lightweight Multi-person Total Motion Capture Using Sparse Multi-view Cameras
[article]
2021
arXiv
pre-print
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To overcome these challenges above, we contribute a lightweight total motion capture system for multi-person interactive scenarios using only sparse multi-view cameras. ...
The results and experiments show that our method achieves more accurate results than existing methods under sparse-view setups. ...
Even though these methods are able to capture 3D human poses using skeletons, they cannot reconstruct full body behaviours, i.e., facial expressions, hand motions, and body surfaces.
3D Hand Reconstruction ...
arXiv:2108.10378v1
fatcat:3sqrnawevrcwfozjjyuidlz42u
Self-Supervised 3D Keypoint Learning for Ego-motion Estimation
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:1912.03426v2 fatcat:e3nnnvognzglngxu6cm5ynxgnyOther Versions
We jointly learn keypoint and depth estimation networks by combining appearance and geometric matching via a differentiable structure-from-motion module based on Procrustean residual pose correction. ...
We describe how our self-supervised keypoints can be integrated into state-of-the-art visual odometry frameworks for robust and accurate ego-motion estimation of autonomous vehicles in real-world conditions ...
To alleviate the limitation of traditional PnP and allow end-to-end learning, we show how the initial pose estimate can be used to derive a 3D loss based on 3D-3D correspondences. ...
arXiv:1912.03426v3
fatcat:sxfvfyh75beivbiuzvb7prx2gq
Mobile Robot Simultaneous Localization and Mapping Based on a Monocular Camera
2016
Journal of Robotics
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In the tracking thread, a ground feature-based pose estimation method is employed to initialize the algorithm for the constraint moving of the mobile robot. ...
This paper proposes a novel monocular vision-based SLAM (Simultaneous Localization and Mapping) algorithm for mobile robot. ...
It is worth noting that projection of a 3D point in the sparse map is generally inconsistent with the corresponding feature point due to inaccuracy involved in feature finding, pose estimation, and so ...
doi:10.1155/2016/7630340
fatcat:udba7l2qm5c45drafo2vr2w5ma
Trajectory planning for monocular SLAM based exploration system
2015
Proceedings of the 2015 Conference on Advances In Robotics - AIR '15
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In VSLAM, the objective is to estimate the trajectory of camera and simultaneously identify 3D feature points and build a map, using camera as a depth sensor. ...
As a consequence of this motion planning framework we are able to automate SLAM and generate automated monocular SLAM maps of an indoor lab area. ...
The camera pose, estimated using motion model is updated by Tracker and the subsequent triangulation of 3D map points depends on pose of the camera. ...
doi:10.1145/2783449.2783476
dblp:conf/air/UpadhyayDSK15
fatcat:ghvo57pwzncwfoghlypvylvuhm
Multi-Sensor Fusion Self-Supervised Deep Odometry and Depth Estimation
2022
Remote Sensing
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We then join deep visual-inertial odometry (DeepVIO) with depth estimation by using sparse depth and the pose from DeepVIO pipeline to align the scale of the depth prediction with the triangulated point ...
to produce the sparse depth and pose with absolute scale. ...
Perspective-n-Point (PnP) is used to solve camera pose given 3D-2D correspondences when the camera motion is pure rotation or the camera translation, tinily. ...
doi:10.3390/rs14051228
fatcat:srqcx7oo4fhztjq4qrutqosaau
EventCap: Monocular 3D Capture of High-Speed Human Motions using an Event Camera
[article]
2019
arXiv
pre-print
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In this paper, we propose EventCap --- the first approach for 3D capturing of high-speed human motions using a single event camera. ...
Our method combines model-based optimization and CNN-based human pose detection to capture high-frequency motion details and to reduce the drifting in the tracking. ...
Second, we estimate the 3D motion of the human actor using a batchbased optimization algorithm. ...
arXiv:1908.11505v1
fatcat:wr36edgfuncpxkl3spr4pbiqcu
EventCap: Monocular 3D Capture of High-Speed Human Motions Using an Event Camera
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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The file type is application/pdf.
In this paper, we propose EventCap -the first approach for 3D capturing of high-speed human motions using a single event camera. ...
Our method combines model-based optimization and CNNbased human pose detection to capture high-frequency motion details and to reduce the drifting in the tracking. ...
Second, we estimate the 3D motion of the human actor using a batchbased optimization algorithm. ...
doi:10.1109/cvpr42600.2020.00502
dblp:conf/cvpr/XuXGHFT20
fatcat:v3j6xqdmcjei5gd6tm7mov7kje
Leveraging Photometric Consistency over Time for Sparsely Supervised Hand-Object Reconstruction
[article]
2020
arXiv
pre-print
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We achieve state-of-the-art results on 3D hand-object reconstruction benchmarks and demonstrate that our approach allows us to improve the pose estimation accuracy by leveraging information from neighboring ...
Our model is trained end-to-end on color images to jointly reconstruct hands and objects in 3D by inferring their poses. ...
Then, we focus on methods using motion and photometric cues for self-supervision, in particular in the context of human body pose estimation. Hand and object pose estimation. ...
arXiv:2004.13449v1
fatcat:gky7kjfxkfa4plfoh7be6icn6y
Leveraging Photometric Consistency Over Time for Sparsely Supervised Hand-Object Reconstruction
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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We achieve state-of-the-art results on 3D hand-object reconstruction benchmarks and demonstrate that our approach allows us to improve the pose estimation accuracy by leveraging information from neighboring ...
Our model is trained end-to-end on color images to jointly reconstruct hands and objects in 3D by inferring their poses. ...
Then, we focus on methods using motion and photometric cues for self-supervision, in particular in the context of human body pose estimation. Hand and object pose estimation. ...
doi:10.1109/cvpr42600.2020.00065
dblp:conf/cvpr/HassonTBLPS20
fatcat:unt2mamyovbibml27ors23p4ru
Joint Spatio-temporal Depth Features Fusion Framework for 3D Structure Estimation in Urban Environment
[chapter]
2012
Lecture Notes in Computer Science
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Our idea is to introduce the monocular depth cues that exist in a single image, and add time constraints on the estimated 3D structure. ...
Temporal depth information is obtained via sparse optical flow based structure from motion approach. That allows decreasing the estimation ambiguity by forcing some constraints on camera motion. ...
Temporal depth features are obtained using a sparse optical flow based structure from motion technique. ...
doi:10.1007/978-3-642-33885-4_53
fatcat:ffpodhncbfejhbxyhlkjzxairq
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