Results 11 to 20 of about 14,152 (262)
Robust camera pose estimation by viewpoint classification using deep learning
Computational Visual Media, 2016 Camera pose estimation with respect to target scenes is an important technology for superimposing virtual information in augmented reality (AR). However, it is difficult to estimate the camera pose for all possible view angles because feature descriptors
Yoshikatsu Nakajima, Hideo Saito
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IMPROVING CAMERA POSE ESTIMATION USING SWARM PARTICLE ALGORITHMS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Most computer vision and photogrammetry applications rely on accurately estimating the camera pose, such as visual navigation, motion tracking, stereo photogrammetry, and structure from motion.
A. Elashry, C. Toth
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, 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 ...
Langerman, Jack +5 more
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Evaluation of Camera Pose Estimation Using Human Head Pose Estimation
SN Computer Science, 2023 AbstractWe 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 head, without the need for depth information. The approach is applicable to single cameras or
Robert Fischer +2 more
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RELATIVE CAMERA POSE ESTIMATION METHOD USING OPTIMIZATION ON THE MANIFOLD [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 To solve the problem of relative camera pose estimation, a method using optimization with respect to the manifold is proposed. Firstly from maximum-a-posteriori (MAP) model to nonlinear least squares (NLS) model, the general state estimation model using ...
C. Cheng, X. Hao, J. Li, J. Li
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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.
C. Olsson, F. Kahl, M. Oskarsson
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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
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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
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DiffPoseNet: Direct Differentiable Camera Pose Estimation
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Current deep neural network approaches for camera pose estimation rely on scene structure for 3D motion estimation, but this decreases the robustness and thereby makes cross-dataset generalization difficult. In contrast, classical approaches to structure from motion estimate 3D motion utilizing optical flow and then compute depth.
Parameshwara, Chethan M. +4 more
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Edge-Based Meta-ICP Algorithm for Reliable Camera Pose Estimation
IEEE Access, 2021 Camera pose estimation is crucial for 3D surface reconstruction and augmented reality applications. For systems equipped with RGB-D sensors, the corresponding transformation between frames can be effectively estimated using the iterative closest point ...
Chun-Wei Chen +2 more
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