Results 11 to 20 of about 20,190 (304)
Evaluation of Camera Pose Estimation Using Human Head Pose Estimation [PDF]
SN Computer Science, 2023 We introduce and evaluate a novel camera pose estimation framework that uses the human head as a calibration object. The proposed method facilitates extrinsic calibration from 2D input images (NIR and/or RGB), while merely relying on the detected human ...
Margrit Gelautz +5 more
core +2 more sources
PhD Forum: Camera Pose Estimation Suitable for Smart Cameras [PDF]
Proceedings of the 11th International Conference on Distributed Smart Cameras, 2017 International audienceCamera pose estimation across video sequences is an important issue under several computer vision applications. In previous work, the most popular approach consists on optimization techniques applied over 2D/3D point correspondences
Abiel Aguilar-González +5 more
core +2 more sources
Markerless Camera Pose Estimation - An Overview [PDF]
, 2011 As shown by the human perception, a correct interpretation of a 3D scene on the basis of a 2D image is possible without markers. Solely by identifying natural features of different objects, their locations and orientations on the image can be identified.
Pagani, Alain +2 more
core +4 more sources
Camera Pose Estimation using Human Head Pose Estimation
Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2022 This paper presents a novel framework for camera pose estimation using the human head as a calibration object. The proposed approach enables extrinsic calibration based on 2D input images (RGB and/or NIR), without any need for additional calibration ...
Margrit Gelautz +5 more
core +2 more sources
Multi-camera head pose estimation
Machine Vision and Applications, 2012 Estimating people's head pose is an important problem, for which many solutions have been proposed. Most existing solutions are based on the use of a single camera and assume that the head is confined in a relatively small region of space.
Munoz-Salinas, Rafael +3 more
core +2 more sources
Camera Pose Estimation with Semantic 3D Model [PDF]
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019 International audienceIn computer vision, estimating camera pose from correspondences between 3D geometric entities and their projections into the image is a widely investigated problem.
Vincent Gaudilliere +5 more
core +3 more sources
CoRR, 2021 One of the key criticisms of deep learning is that large amounts of expensive and difficult-to-acquire training data are required in order to train models with high performance and good generalization capabilities. Focusing on the task of monocular camera pose estimation via scene coordinate regression (SCR), we describe a novel method, Domain ...
Jack Langerman +5 more
openaire +2 more sources
Optimal Estimation of Perspective Camera Pose [PDF]
18th International Conference on Pattern Recognition (ICPR'06), 2006 In this paper we propose a practical and efficient method for finding the globally optimal solution to the problem of camera pose estimation for calibrated cameras. While traditional methods may get trapped in local minima, due to the non-convexity of the problem, we have developed an approach that guarantees global optimality.
Carl Olsson +2 more
openaire +1 more source
A New Pose Estimation Algorithm Using a Perspective-Ray-Based Scaled Orthographic Projection with Iteration. [PDF]
PLoS ONE, 2015 Pose estimation aims at measuring the position and orientation of a calibrated camera using known image features. The pinhole model is the dominant camera model in this field.
Pengfei Sun +3 more
doaj +1 more source
Deep Photo-Geometric Loss for Relative Camera Pose Estimation
IEEE Access, 2023 CNN-based absolute camera pose estimation methods lack scene generalizability as the network is trained with scene-specific parameters. In this paper, we aim to solve the scene generalizability problem in 6-DoF camera pose estimation using a novel deep ...
Yongju Cho +5 more
doaj +1 more source