Estimation of automotive pitch, yaw, and roll using enhanced phase correlation on multiple far-field windows

Barnada, Marc; Conrad, Christian; Bradler, Henry; Ochs, Matthias; Mester, Rudolf

doi:10.1109/ivs.2015.7225731

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…They deal with a wide range of applications such that the lane keeping assist systems [4], the obstacle detection [5], the parking assistance, etc. Other works have addressed the estimation of the vehicle dynamics as in [6] were the authors used vision to estimate the vehicle Euler angles. Finaly, soon, cameras could replace most of the embedded sensors such that gyroscopes, accelerometers, wheel speed sensors, etc.…”

Section: Motivation and Problem Statementmentioning

confidence: 99%

Image-Based Lateral Position, Steering Behavior Estimation, and Road Curvature Prediction for Motorcycles

Damon

Hadj-Abdelkader

Arioui

2018

IEEE Robot. Autom. Lett.

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This paper presents an image-based approach to simultaneously estimate the lateral position of a powered-two wheeled vehicle on the road, its steering behavior and predict the road curvature ahead of the motorcycle. This work is based on the inverse perspective mapping technique combined with a road lanes detection algorithm capable of detecting straight and curved lanes. Then, a clothoid model is used to extract pertinent information from the detected road markers. Finally, the performance of the proposed approach is illustrated through simulations carried out with the well-known motorcycle simulator "BikeSim". The results are very promising since the algorithm is capable of estimating, in real time, the road geometry and the vehicle location with a better accuracy than the one given by the commercial GPS.

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Section: Motivation and Problem Statementmentioning

confidence: 99%

Image-Based Lateral Position, Steering Behavior Estimation, and Road Curvature Prediction for Motorcycles

Damon

Hadj-Abdelkader

Arioui

2018

IEEE Robot. Autom. Lett.

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“…Effendi and Jarvis [24] estimated camera ego-motion using phase correlation, however, this method requires a plane, such as table plane, to be discovered in images. Other studies [25,26] apply phase correlation using small matching window and then estimated the geometric transformation based on corresponding result from phase correlation matching. These approaches have the similar limitation to most feature-based methods as they are based on local grey value distribution while regardless of overall structural similarity.…”

Section: Related Workmentioning

confidence: 99%

The Extension of Phase Correlation to Image Perspective Distortions Based on Particle Swarm Optimization

Wan

Wang

2019

Sensors

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Phase correlation is one of the widely used image registration method in medical image processing and remote sensing. One of the main limitations of the phase correlation-based registration method is that it can only cope with Euclidean transformations, such as translation, rotation and scale, which constrain its application in wider fields, such as multi-view image matching, image-based navigation, etc. In this paper, we extended the phase correlation to perspective transformation by the combination of particle swarm optimization. Inspired by optic lens alignment based on interference, we propose to use the quality of PC fringes as the similarity, and then the aim of registration is to search for the optimized geometric transformation operator, which obtain the maximize value of PC-based similarity function through particle swarm optimization approach. The proposed method is validated by image registration experiments using simulated terrain shading, texture and natural landscape images containing different challenges, including illumination variation, lack of texture, motion blur, occlusion and geometric distortions. Further, image-based navigation experiments are carried out to demonstrate that the proposed method is able to correctly recover the trajectory of camera using multimodal target and reference image. Even under great radiometric and geometric distortions, the proposed method is able to achieve 0.1 sub-pixel matching accuracy on average while other methods fail to find the correspondence.

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“…On the same topic, some works have addressed P4WV orientation estimation. We can cite [12], where the author introduced an algorithm to simultaneously estimate the vehicle roll, yaw and pitch angles with a monocular camera. Nevertheless, this technique works for a small roll range and consequently, cannot be used for motorcycle estimation purposes.…”

Section: Motivation and Problem Statementmentioning

confidence: 99%

Inverse Perspective Mapping Roll Angle Estimation for Motorcycles

Damon¹,

Hadj-Abdelkader²,

Arioui³

2018

2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)

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This paper presents an image-based approach to estimate the motorcycle roll angle. The algorithm estimates directly the absolute roll to the road plane by means of a basic monocular camera. This means that the estimated roll angle is not affected by the road bank which is often a problem for vehicle observation and control purposes. For each captured image, the algorithm uses a numeric roll loop based on some simple knowledge of the road geometry. For each iteration, a birdeye-view of the road is generated with the inverse perspective mapping technique. Then, a road marker filter associated with the well-known clothoid model are used respectively to track the road separation lanes and approximate them with mathematical functions. Finally, the algorithm computes two distinct areas between the two-road separation lanes. Its performances are tested by means of the motorcycle simulator BikeSim. This approach is very promising since it does not require any vehicle or tire model and is free of restrictive assumptions on the dynamics.

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Estimation of automotive pitch, yaw, and roll using enhanced phase correlation on multiple far-field windows

Cited by 7 publications

References 10 publications

Image-Based Lateral Position, Steering Behavior Estimation, and Road Curvature Prediction for Motorcycles

Image-Based Lateral Position, Steering Behavior Estimation, and Road Curvature Prediction for Motorcycles

The Extension of Phase Correlation to Image Perspective Distortions Based on Particle Swarm Optimization

Inverse Perspective Mapping Roll Angle Estimation for Motorcycles

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