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Sensors (Basel) ; 21(17)2021 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-34502780


When a traditional visual SLAM system works in a dynamic environment, it will be disturbed by dynamic objects and perform poorly. In order to overcome the interference of dynamic objects, we propose a semantic SLAM system for catadioptric panoramic cameras in dynamic environments. A real-time instance segmentation network is used to detect potential moving targets in the panoramic image. In order to find the real dynamic targets, potential moving targets are verified according to the sphere's epipolar constraints. Then, when extracting feature points, the dynamic objects in the panoramic image are masked. Only static feature points are used to estimate the pose of the panoramic camera, so as to improve the accuracy of pose estimation. In order to verify the performance of our system, experiments were conducted on public data sets. The experiments showed that in a highly dynamic environment, the accuracy of our system is significantly better than traditional algorithms. By calculating the RMSE of the absolute trajectory error, we found that our system performed up to 96.3% better than traditional SLAM. Our catadioptric panoramic camera semantic SLAM system has higher accuracy and robustness in complex dynamic environments.

Algoritmos , Semântica
Sensors (Basel) ; 21(12)2021 Jun 10.
Artigo em Inglês | MEDLINE | ID: mdl-34200669


The omnidirectional camera, having the advantage of broadening the field of view, realizes 360° imaging in the horizontal direction. Due to light reflection from the mirror surface, the collinearity relation is altered and the imaged scene has severe nonlinear distortions. This makes it more difficult to estimate the pose of the omnidirectional camera. To solve this problem, we derive the mapping from omnidirectional camera to traditional camera and propose an omnidirectional camera linear imaging model. Based on the linear imaging model, we improve the EPnP algorithm to calculate the omnidirectional camera pose. To validate the proposed solution, we conducted simulations and physical experiments. Results show that the algorithm has a good performance in resisting noise.

Algoritmos , Modelos Lineares
Appl Opt ; 59(22): 6476-6483, 2020 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-32749345


The two-dimensional Fourier-transform-based integration algorithm is widely used in shape or wavefront reconstruction from gradients. However, its reconstruction accuracy is limited by the truncation error of the difference model. The truncation error is affected by the distribution of the sampling points. It increases when the sampling points are unevenly distributed and arranged irregularly. For improving, a novel way to calculate the difference is proposed based on Taylor expansion theory of binary functions. The first-order partial derivative terms are used to estimate the second- and third-order partial derivative terms for reducing the truncation error. The proposed difference model is applied to Fourier-transform-based integration. The reconstruction results show that it can get better results when the sampling points are irregularly distributed.

Appl Opt ; 57(9): 2155-2164, 2018 Mar 20.
Artigo em Inglês | MEDLINE | ID: mdl-29604005


This paper focuses on camera calibration with one-dimensional (1D) objects, and novel methods are proposed in this paper. Different from the known 1D object-based camera calibration algorithms, which define the camera coordinate system as the world coordinate system, we assume that the 1D calibration object is located along the X axis of the world coordinate system. Based on this new model, a 3×2 1D homography is defined to relate the points in the 1D objects to the perspective image points thereof. Then, the basic constraint for camera calibration using 1D objects from a single image is derived. Subsequently, two existing motions, namely, rotating around a fixed point and moving on a plane, are discussed, and new algorithms are proposed. In our methods, if the number of points in the 1D objects is more than three, more compact constraints can be obtained when the 1D objects rotate around a fixed point. In the case of planar motion, the estimation of vanishing points is not needed, and the calibration accuracy is significantly improved. Finally, both computer simulations and experiments are performed to validate the effectiveness and robustness of our algorithms.

Opt Express ; 24(12): 13288-302, 2016 Jun 13.
Artigo em Inglês | MEDLINE | ID: mdl-27410346


The Greenwood frequency (GF) is influential in performance improvement for the coherent free space optical communications (CFSOC) system with a closed-loop adaptive optics (AO) unit. We analyze the impact of tilt and high-order aberrations on the mixing efficiency (ME) and bit-error-rate (BER) under different GF. The root-mean-square value (RMS) of the ME related to the RMS of the tilt aberrations, and the GF is derived to estimate the volatility of the ME. Furthermore, a numerical simulation is applied to verify the theoretical analysis, and an experimental correction system is designed with a double-stage fast-steering-mirror and a 97-element continuous surface deformable mirror. The conclusions of this paper provide a reference for designing the AO system for the CFSOC system.