Automatic camera orientation estimation for a partially calibrated camera above a plane with a line at known planar distance
- URL: http://arxiv.org/abs/2507.20689v1
- Date: Mon, 28 Jul 2025 10:17:13 GMT
- Title: Automatic camera orientation estimation for a partially calibrated camera above a plane with a line at known planar distance
- Authors: Gergely Dinya, Anna Gelencsér-Horváth,
- Abstract summary: We present a derivation for estimating the roll and pitch orientation of a partially calibrated camera mounted above a planar surface.<n>We assume known intrinsic parameters and a fixed height between the camera and the observed plane.<n>We estimate the roll and pitch angles via inverse projection geometry.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: We present a derivation for estimating the roll and pitch orientation of a partially calibrated camera mounted above a planar surface, using minimal scene information. Specifically, we assume known intrinsic parameters and a fixed height between the camera and the observed plane. By detecting a single straight reference line at a known planar distance -- such as the edge between a floor and a wall -- we estimate the roll and pitch angles via inverse projection geometry. The method leverages geometric constraints and the camera model, including lens distortion correction. This approach is suitable for scenarios where full calibration is impractical and offers a lightweight alternative for multi-camera systems operating in constrained environments.
Related papers
- A Simple Algebraic Solution for Estimating the Pose of a Camera from Planar Point Features [0.3686808512438362]
This paper presents a simple method to estimate the pose of a camera relative to a planar target from $n geq 4$ reference points.<n>The accuracy and robustness of the approach are validated through extensive experiments.
arXiv Detail & Related papers (2025-08-03T16:47:34Z) - Dynamic View Synthesis from Small Camera Motion Videos [56.359460602781304]
We present a novel view synthesis for dynamic $3$D scenes based on distribution-based depth regularization.<n>We also introduce constraints that enforce the volume density of spatial points before the object boundary along the ray to be near zero, ensuring that our model learns the correct geometry of the scene.<n>We conduct extensive experiments to demonstrate the effectiveness of our approach in representing scenes with small camera motion input, and our results compare favorably to state-of-the-art methods.
arXiv Detail & Related papers (2025-06-29T09:17:55Z) - Single-Scanline Relative Pose Estimation for Rolling Shutter Cameras [56.39904484784127]
We propose an approach for estimating the relative pose between rolling shutter cameras using the intersections of line projections with a single scanline per image.<n>Alternatively, scanlines can be selected within a single image, enabling single-view relative pose estimation for scanlines of rolling shutter cameras.
arXiv Detail & Related papers (2025-06-27T10:00:21Z) - AlignDiff: Learning Physically-Grounded Camera Alignment via Diffusion [0.5277756703318045]
We introduce a novel framework that addresses camera intrinsic and extrinsic parameters using a generic ray camera model.<n>Unlike previous approaches, AlignDiff shifts focus from semantic to geometric features, enabling more accurate modeling of local distortions.<n>Our experiments demonstrate that the proposed method significantly reduces the angular error of estimated ray bundles by 8.2 degrees and overall calibration accuracy, outperforming existing approaches on challenging, real-world datasets.
arXiv Detail & Related papers (2025-03-27T14:59:59Z) - In Flight Boresight Rectification for Lightweight Airborne Pushbroom Imaging Spectrometry [1.5624421399300306]
Many hyperspectral sensors use a linear array or 'push-broom' scanning design.
We propose a method for tie point extraction and camera calibration for 'push-broom' hyperspectral sensors.
We demonstrate that our approach allows for the automatic calibration of airborne systems with hyperspectral cameras.
arXiv Detail & Related papers (2024-09-10T13:55:47Z) - Single-image camera calibration with model-free distortion correction [0.0]
This paper proposes a method for estimating the complete set of calibration parameters from a single image of a planar speckle pattern covering the entire sensor.
The correspondence between image points and physical points on the calibration target is obtained using Digital Image Correlation.
At the end of the procedure, a dense and uniform model-free distortion map is obtained over the entire image.
arXiv Detail & Related papers (2024-03-02T16:51:35Z) - Virtual Inverse Perspective Mapping for Simultaneous Pose and Motion
Estimation [5.199765487172328]
We propose an automatic method for pose and motion estimation against a ground surface for a ground-moving robot-mounted monocular camera.
The framework adopts a semi-dense approach that benefits from both a feature-based method and an image-registration-based method.
arXiv Detail & Related papers (2023-03-09T11:45:00Z) - How to Calibrate Your Event Camera [58.80418612800161]
We propose a generic event camera calibration framework using image reconstruction.
We show that neural-network-based image reconstruction is well suited for the task of intrinsic and extrinsic calibration of event cameras.
arXiv Detail & Related papers (2021-05-26T07:06:58Z) - Calibrated and Partially Calibrated Semi-Generalized Homographies [65.29477277713205]
We propose the first minimal solutions for estimating the semi-generalized homography given a perspective and a generalized camera.
The proposed solvers are stable and efficient as demonstrated by a number of synthetic and real-world experiments.
arXiv Detail & Related papers (2021-03-11T08:56:24Z) - Wide-angle Image Rectification: A Survey [86.36118799330802]
wide-angle images contain distortions that violate the assumptions underlying pinhole camera models.
Image rectification, which aims to correct these distortions, can solve these problems.
We present a detailed description and discussion of the camera models used in different approaches.
Next, we review both traditional geometry-based image rectification methods and deep learning-based methods.
arXiv Detail & Related papers (2020-10-30T17:28:40Z) - From Planes to Corners: Multi-Purpose Primitive Detection in Unorganized
3D Point Clouds [59.98665358527686]
We propose a new method for segmentation-free joint estimation of orthogonal planes.
Such unified scene exploration allows for multitudes of applications such as semantic plane detection or local and global scan alignment.
Our experiments demonstrate the validity of our approach in numerous scenarios from wall detection to 6D tracking.
arXiv Detail & Related papers (2020-01-21T06:51:47Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.