Robust Coordinate System Research Articles

Skeleton-based coordinate system construction method for non-cooperative targets

Due to the lack of structure and part information in non-cooperative targets, the task of pose estimation suffers from unstable and unreliable initial coordinate system. In this paper, we introduce a curve-skeleton-based method to construct the robust coordinate system automatically for non-cooperative targets. First, a nonmanifold-Laplacian-based method is proposed to extract the curve skeleton from point clouds. The proposed method solves the over-contraction problem while preserves the topology and structure of skeleton well during point clouds contraction. Additionally, we create the skeleton graph to detect the skeleton structure and key points automatically. Then, the detected skeleton feature is used to construct target coordinate system, and improve the stability and robustness. Specifically, a real-scan dataset is constructed in this paper, and the proposed point cloud contraction method outperforms previous methods in structural representation and visualization. The mean rotation error of proposed coordinate system construct method performs 0.1249° and 1.2135° in 0%–30% noise ratio of distortions and outliers, and performs 7.04° and 4.21° in real-scan aircraft and satellite datasets. The results in complete and incomplete datasets verify the robustness and reliability of our skeleton-based coordinate system.

Development and validation of a robust patellar reference coordinate system for biomechanical and clinical studies

BackgroundThis study aimed to develop and validate a reference coordinate system for the human patella, based on the registration of bony landmarks on a computed tomography (CT) scan. MethodsThirty-three native cadaveric specimens were scanned, and an observer marked a set of seven anatomical landmarks on each of them. Such markers were used to define the reference coordinate system. In order to validate its robustness, statistical distribution of the point registration was then studied. Afterwards, three different observers marked the anatomical landmarks on a sub-sample of six specimens and the intra-observer and inter-observer variability of the point registration was performed. ResultsResults of this study showed the highest values to be 1.46 mm (intra) and 4.08 mm (inter), both observed for the patellar ridge top. The intra-class correlation coefficient (ICC) for inter-observer variability ranked higher than 0.8 for all the landmarks used for the identification of the reference frame, and ranged from 0.4–0.9 for other landmarks. ConclusionsThis study demonstrates low intra-observer and inter-observer variability in the CT registration of landmarks that define and validate a robust coordinate system of the patella that could be used to perform accurate biomechanical and clinical studies.

Face Recognition with Occlusion using a wireframe model and Support Vector Machine

This paper proposes a face recognition system with the capacity of achieving high recognition rates, even if the face image presents significant occlusion, using a wireframe model and a Facefit tool that acquires a coordinate system with fiducial points that characterize the facial parts. Thereby, the occlusions are emulated by the selection of points that represent four cases of partial blockage of the face such as: occlusion in eyes area, occlusion in the area of mouth and occlusion in left and right part of face in a separately way. Computer simulations show that the proposed system provides recognition rates higher than 95% in each case, providing also stability to the identification system. Thus, the wireframe model presents a robust coordinate system that even in complex cases, as data loss, is able to obtain a fairly good recognition rate.