scholarly journals Automatic Multi-Camera Extrinsic Parameter Calibration Based on Pedestrian Torsors †

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4989
Author(s):  
Truong ◽  
Philips ◽  
Deligiannis ◽  
Abrahamyan ◽  
Guan
Keyword(s):  
Brute Force ◽  
Camera Network ◽  
Extrinsic Calibration ◽  
Multiple Camera ◽  
Extrinsic Parameter ◽  
Extrinsic Parameters ◽  
Brute Force Method ◽  
Controlled Environments ◽  
Novel Method ◽  
Fully Automatic

Extrinsic camera calibration is essential for any computer vision task in a camera network. Typically, researchers place a calibration object in the scene to calibrate all the cameras in a camera network. However, when installing cameras in the field, this approach can be costly and impractical, especially when recalibration is needed. This paper proposes a novel, accurate and fully automatic extrinsic calibration framework for camera networks with partially overlapping views. The proposed method considers the pedestrians in the observed scene as the calibration objects and analyzes the pedestrian tracks to obtain extrinsic parameters. Compared to the state of the art, the new method is fully automatic and robust in various environments. Our method detect human poses in the camera images and then models walking persons as vertical sticks. We apply a brute-force method to determines the correspondence between persons in multiple camera images. This information along with 3D estimated locations of the top and the bottom of the pedestrians are then used to compute the extrinsic calibration matrices. We also propose a novel method to calibrate the camera network by only using the top and centerline of the person when the bottom of the person is not available in heavily occluded scenes. We verified the robustness of the method in different camera setups and for both single and multiple walking people. The results show that the triangulation error of a few centimeters can be obtained. Typically, it requires less than one minute of observing the walking people to reach this accuracy in controlled environments. It also just takes a few minutes to collect enough data for the calibration in uncontrolled environments. Our proposed method can perform well in various situations such as multi-person, occlusions, or even at real intersections on the street.

scholarly journals A Novel Method for Intrinsic and Extrinsic Parameters Estimation by Solving Perspective-Three-Point Problem with Known Camera Position

2021 ◽  
Vol 11 (13) ◽  
pp. 6014
Author(s):  
Kai Guo ◽  
Hu Ye ◽  
Junhao Gu ◽  
Honglin Chen
Keyword(s):  
Parameter Estimation ◽  
Image Plane ◽  
Image Resolution ◽  
Parameters Estimation ◽  
Position Information ◽  
Virtual Camera ◽  
Extrinsic Parameter ◽  
Extrinsic Parameters ◽  
Novel Method ◽  
Camera Position

The aim of the perspective-three-point (P3P) problem is to estimate extrinsic parameters of a camera from three 2D–3D point correspondences, including the orientation and position information. All the P3P solvers have a multi-solution phenomenon that is up to four solutions and needs a fully calibrated camera. In contrast, in this paper we propose a novel method for intrinsic and extrinsic parameter estimation based on three 2D–3D point correspondences with known camera position. Our core contribution is to build a new, virtual camera system whose frame and image plane are defined by the original 3D points, to build a new, intermediate world frame by the original image plane and the original 2D image points, and convert our problem to a P3P problem. Then, the intrinsic and extrinsic parameter estimation is to solve frame transformation and the P3P problem. Lastly, we solve the multi-solution problem by image resolution. Experimental results show its accuracy, numerical stability and uniqueness of the solution for intrinsic and extrinsic parameter estimation in synthetic data and real images.

scholarly journals CoMask: Corresponding Mask-Based End-to-End Extrinsic Calibration of the Camera and LiDAR

2020 ◽  
Vol 12 (12) ◽  
pp. 1925
Author(s):  
Lu Yin ◽  
Bin Luo ◽  
Wei Wang ◽  
Huan Yu ◽  
Chenjie Wang ◽  
...  
Keyword(s):  
Optimization Problem ◽  
Autonomous Driving ◽  
Noise Resistance ◽  
Extrinsic Calibration ◽  
Manual Intervention ◽  
Extrinsic Parameters ◽  
Fully Automatic ◽  
End To End ◽  
Special Environment ◽  
3D Lidar

The integration of the camera and LiDAR has played an important role in the field of autonomous driving, for example in visual–LiDAR SLAM and 3D environment fusion perception, which rely on precise geometrical extrinsic calibration. In this paper, we proposed a fully automatic end-to-end method based on the 3D–2D corresponding mask (CoMask) to directly estimate the extrinsic parameters with high precision. Simple subtraction was applied to extract the candidate point cluster from the complex background, and then 3D LiDAR points located on checkerboard were selected and refined by spatial growth clustering. Once the distance transform of 2D checkerboard mask was generated, the extrinsic calibration of the two sensors could be converted to 3D–2D mask correspondence alignment. A simple but efficient strategy combining the genetic algorithm with the Levenberg–Marquardt method was used to solve the optimization problem globally without any initial estimates. Both simulated and realistic experiments showed that the proposed method could obtain accurate results without manual intervention, special environment setups, or prior initial parameters. Compared with the state of the art, our method has obvious advantages in accuracy, robustness, and noise resistance. Our code is open-source on GitHub.

scholarly journals Sub-Frame Evaluation of Frame Synchronization for Camera Network Using Linearly Oscillating Light Spot

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6148
Author(s):  
Hyuno Kim ◽  
Masatoshi Ishikawa
Keyword(s):  
Visual Information ◽  
Evaluation Method ◽  
Measurement Instrument ◽  
Light Spot ◽  
Estimation Accuracy ◽  
Accurate Data ◽  
Frame Synchronization ◽  
Camera Network ◽  
Novel Method ◽  
Synchronization Accuracy

Precisely evaluating the frame synchronization of the camera network is often required for accurate data fusion from multiple visual information. This paper presents a novel method to estimate the synchronization accuracy by using inherent visual information of linearly oscillating light spot captured in the camera images instead of using luminescence information or depending on external measurement instrument. The suggested method is compared to the conventional evaluation method to prove the feasibility. Our experiment result implies that the estimation accuracy of the frame synchronization can be achieved in sub-millisecond order.

scholarly journals Extrinsic LiDAR/Ground Calibration Method Using 3D Geometrical Plane-Based Estimation

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2841
Author(s):  
Mohammad Ali Zaiter ◽  
Régis Lherbier ◽  
Ghaleb Faour ◽  
Oussama Bazzi ◽  
Jean-Charles Noyer
Keyword(s):  
Ground Plane ◽  
Ground Surface ◽  
Real Data ◽  
Calibration Method ◽  
Parameters Estimation ◽  
Parameters Optimization ◽  
Method Performance ◽  
Extrinsic Calibration ◽  
Extrinsic Parameters ◽  
The Stability

This paper details a new extrinsic calibration method for scanning laser rangefinder that is precisely focused on the geometrical ground plane-based estimation. This method is also efficient in the challenging experimental configuration of a high angle of inclination of the LiDAR. In this configuration, the calibration of the LiDAR sensor is a key problem that can be be found in various domains and in particular to guarantee the efficiency of ground surface object detection. The proposed extrinsic calibration method can be summarized by the following procedure steps: fitting ground plane, extrinsic parameters estimation (3D orientation angles and altitude), and extrinsic parameters optimization. Finally, the results are presented in terms of precision and robustness against the variation of LiDAR’s orientation and range accuracy, respectively, showing the stability and the accuracy of the proposed extrinsic calibration method, which was validated through numerical simulation and real data to prove the method performance.

scholarly journals Optimization of Composite Fracture Properties: Method, Validation, and Applications

2016 ◽  
Vol 83 (7) ◽  
Author(s):  
Grace X. Gu ◽  
Leon Dimas ◽  
Zhao Qin ◽  
Markus J. Buehler
Keyword(s):  
Optimization Algorithm ◽  
Material Properties ◽  
Building Blocks ◽  
Test Case ◽  
Brute Force ◽  
Vast Number ◽  
Engineering Problems ◽  
Brute Force Method ◽  
Optimization Parameters ◽  
Underlying Mechanisms

A paradigm in nature is to architect composites with excellent material properties compared to its constituents, which themselves often have contrasting mechanical behavior. Most engineering materials sacrifice strength for toughness, whereas natural materials do not face this tradeoff. However, biology's designs, adapted for organism survival, may have features not needed for some engineering applications. Here, we postulate that mimicking nature's elegant use of multimaterial phases can lead to better optimization of engineered materials. We employ an optimization algorithm to explore and design composites using soft and stiff building blocks to study the underlying mechanisms of nature's tough materials. For different applications, optimization parameters may vary. Validation of the algorithm is carried out using a test suite of cases without cracks to optimize for stiffness and compliance individually. A test case with a crack is also performed to optimize for toughness. The validation shows excellent agreement between geometries obtained from the optimization algorithm and the brute force method. This study uses different objective functions to optimize toughness, stiffness and toughness, and compliance and toughness. The algorithm presented here can provide researchers a way to tune material properties for a vast number of engineering problems by adjusting the distribution of soft and stiff materials.

scholarly journals Application of Genetic Algorithm for More Efficient Multi-Layer Thickness Optimization in Solar Cells

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1726
Author(s):  
Premkumar Vincent ◽  
Gwenaelle Cunha Sergio ◽  
Jaewon Jang ◽  
In Man Kang ◽  
Jaehoon Park ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Solar Cells ◽  
Heuristic Method ◽  
Brute Force ◽  
Force Parameter ◽  
Thickness Optimization ◽  
Sweep Method ◽  
Case Scenario ◽  
Force Method ◽  
Brute Force Method

Thin-film solar cells are predominately designed similar to a stacked structure. Optimizing the layer thicknesses in this stack structure is crucial to extract the best efficiency of the solar cell. The commonplace method used in optimization simulations, such as for optimizing the optical spacer layers’ thicknesses, is the parameter sweep. Our simulation study shows that the implementation of a meta-heuristic method like the genetic algorithm results in a significantly faster and accurate search method when compared to the brute-force parameter sweep method in both single and multi-layer optimization. While other sweep methods can also outperform the brute-force method, they do not consistently exhibit 100% accuracy in the optimized results like our genetic algorithm. We have used a well-studied P3HT-based structure to test our algorithm. Our best-case scenario was observed to use 60.84% fewer simulations than the brute-force method.

Stored Response Modeling

1978 ◽  
Vol 100 (2) ◽  
pp. 132-139
Author(s):  
J. Eichler
Keyword(s):  
The State ◽  
Input Vector ◽  
Deterministic System ◽  
Brute Force ◽  
Nonstationary System ◽  
Current State ◽  
Brute Force Method ◽  
Definition Of ◽  
Response Modeling ◽  
Nonstationary Systems

A direct “brute force” method of system identification is presented. The method is based on the definition of a deterministic system and applicable to nonlinear nonstationary systems with measurement noise. The approach is to discretize the state of the system (or equivalent measurable state), the input vector and time (in the case of a nonstationary system). For these discretized sets of values, the response i.e. the state at t + Δt is determined and stored, thus giving a “stored response” model SRM. The response for arbitrary input vector (within the class for which the model was made) is then obtained by interpolating stored responses for the current state vector, input vector and time thus yielding the state at the next Δt. Repeating this procedure produces the model’s dynamic response. The method of building the SRM table and using it is discussed and several examples are given. An optimal control problem is solved using the SRM model.

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