We propose an approach for realizing 3D reconstruction in small field of view or some extreme environments. We combine the stereo vision and the structured light technologies and change the traditional ways of applying them by employing two fiber bundles. The processes of calibration and 3D reconstruction are also introduced. Experiments are performed to verify the feasibility and effectiveness of our proposed approach.
Calibrating a small field camera is a challenging task because the traditional target with visible feature points that fit the limited space is difficult and costly to manufacture. We demonstrate a novel combined target used in camera calibration. The tangent points supplied by one circle located at the center of a square are used as invisible features, and the perspective projection invariance is proved. Both visible and invisible features extracted by the proposed feature extraction algorithm are used to solve the calibration. The target supplies a sufficient number of feature points to satisfy the requirements of calibration within a limited space. Experiments show that the approach can achieve high robustness and considerable accuracy. This approach has potential for computer vision applications particularlv in small fields of view.
For a long time,trouble detection and maintenance of freight cars have been completed manually by inspectors.To realize the transition from manual to computer-based detection and maintenance,we focus on dust collector localization under complex conditions in the trouble of moving freight car detection system.Using mid-level features which are also named flexible edge arrangement(FEA) features,we first build the edge-based 2D model of the dust collectors,and then match target objects by a weighted Hausdorff distance method.The difference is that the constructed weighting function is generated by the FEA features other than specified subjectively,which can truly reflect the most basic property regions of the 3D object.Experimental results indicate that the proposed algorithm has better robustness to variable lighting,different viewing angle,and complex texture,and it shows a stronger adaptive performance.The localization correct rate of the target object is over 90%,which completely meets the need of practical applications.
