A simple solution for the non perspective three point pose problem

Merzban, Mohamed H.; Abdellatif, Mohamed; Abouelsoud, A. A.

doi:10.1109/ic3d.2014.7032594

Cited by 6 publications

(3 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An analytic and non-iterative method is then proposed to solve the coplanar perspective-4-points problem to find [ R CA , t CA ] as described in the previous subsection. There are many classical methods to solve this perspective problem, including the non-iterative method Epnp [29], the iterative linear solution using unbiased statistics [30,31], some simple methods based on P3P problem [32,33] and many linear analytic solutions [34,35,36,37,38] and so on. Compared to these classical methods, the proposed method has the advantage of low computational complexity.…”

Section: Multimodal Sensor Data Processingmentioning

confidence: 99%

A Wireless Visualized Sensing System with Prosthesis Pose Reconstruction for Total Knee Arthroplasty

Jiang

Xiang

Guo

et al. 2019

Sensors

View full text Add to dashboard Cite

The surgery quality of the total knee arthroplasty (TKA) depends on how accurate the knee prosthesis is implanted. The knee prosthesis is composed of the femoral component, the plastic spacer and the tibia component. The instant and kinetic relative pose of the knee prosthesis is one key aspect for the surgery quality evaluation. In this work, a wireless visualized sensing system with the instant and kinetic prosthesis pose reconstruction has been proposed and implemented. The system consists of a multimodal sensing device, a wireless data receiver and a data processing workstation. The sensing device has the identical shape and size as the spacer. During the surgery, the sensing device temporarily replaces the spacer and captures the images and the contact force distribution inside the knee joint prosthesis. It is connected to the external data receiver wirelessly through a 432 MHz data link, and the data is then sent to the workstation for processing. The signal processing method to analyze the instant and kinetic prosthesis pose from the image data has been investigated. Experiments on the prototype system show that the absolute reconstruction errors of the flexion-extension rotation angle (the pitch rotation of the femoral component around the horizontal long axis of the spacer), the internal–external rotation (the yaw rotation of the femoral component around the spacer vertical axis) and the mediolateral translation displacement between the centers of the femoral component and the spacer based on the image data are less than 1.73°, 1.08° and 1.55 mm, respectively. It provides a force balance measurement with error less than ±5 N. The experiments also show that kinetic pose reconstruction can be used to detect the surgery defection that cannot be detected by the force measurement or instant pose reconstruction.

show abstract

Section: Multimodal Sensor Data Processingmentioning

confidence: 99%

A Wireless Visualized Sensing System with Prosthesis Pose Reconstruction for Total Knee Arthroplasty

Jiang

Xiang

Guo

et al. 2019

Sensors

View full text Add to dashboard Cite

show abstract

“…Clipp et al [16] used point features in a mixed number of views, and Dunn et al [17] used similar input data and accelerated the solving speed by using the constraints in proper ways. Discarding the correspondences without projections onto both views of one stereo camera, one can use generalized absolute pose solvers [18,19,20,21,22,23]. To summarize, no prior work addresses stereo relative pose problem for three features with three projections.…”

Section: Related Workmentioning

confidence: 99%

Stereo Relative Pose from Line and Point Feature Triplets

Vakhitov

Lempitsky

Zheng

2018

Computer Vision – ECCV 2018

View full text Add to dashboard Cite

Stereo relative pose problem lies at the core of stereo visual odometry systems that are used in many applications. In this work we present two minimal solvers for the stereo relative pose. We specifically consider the case when a minimal set consists of three point or line features and each of them has three known projections on two stereo cameras. We validate the importance of this formulation for practical purposes in our experiments with motion estimation. We then present a complete classification of minimal cases with three point or line correspondences each having three projections, and present two new solvers that can handle all such cases. We demonstrate a considerable effect from the integration of the new solvers into a visual SLAM system.

show abstract

“…By using the method with the parameterized rotation matrix, the position problem is transformed into an optimization problem of the rotation parameters; subsequently, the polynomial equations of the rotation parameters are solved to obtain the closedform solution to calculate the position [19]- [22]. However, for the method using the points feature of cooperative targets, no matter whether it is an iterative method or a non-iterative method, the n ≥ 3 available target points are required; when the number of target points is below three, the existing measurement method fails, and other solutions must be sought [23]- [25].…”

Section: Introductionmentioning

confidence: 99%

Method for Horizontal Alignment Deviation Measurement Using Binocular Camera Without Common Target

Wang

Shen

et al. 2020

IEEE Access

View full text Add to dashboard Cite

In the application of using binocular camera to measure the horizontal alignment deviation, due to the limited field of view of the camera, it is difficult for each camera to obtain all the target points to determine the position of the parts. To this end, a binocular position measurement model, where each optical camera corresponds to one cooperative target point, is established to determine the horizontal alignment deviation between the upper and lower parts. To overcome the problem of insufficient information in calculating the horizontal alignment deviation, the measurement data of a biaxial inclinometer and laser rangefinder are added. The Monte Carlo method is used to determine the error level for any position and attitude in the measurement range based on past work experience. The high accuracy of the position measurement method (the overall error does not exceed 2 mm) for a binocular camera without a common target meets the actual application requirements. This conclusion is verified by the experimental results. INDEX TERMS Binocular position measurement, horizontal alignment deviation, no common target, biaxial inclinometer, laser ranging, Monte Carlo method

show abstract

A simple solution for the non perspective three point pose problem

Cited by 6 publications

References 11 publications

A Wireless Visualized Sensing System with Prosthesis Pose Reconstruction for Total Knee Arthroplasty

A Wireless Visualized Sensing System with Prosthesis Pose Reconstruction for Total Knee Arthroplasty

Stereo Relative Pose from Line and Point Feature Triplets

Method for Horizontal Alignment Deviation Measurement Using Binocular Camera Without Common Target

Contact Info

Product

Resources

About