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The detection of surrounding vehicles is an essential task in autonomous driving, which has been drawing enormous attention recently. When using laser scanners, L-Shape fitting is a key step for model-based vehicle detection and tracking, which requires thorough investigation and comprehensive research. In this paper, we formulate the L-Shape fitting as an optimization problem. An efficient search...
Place recognition is widely used in the loop closure detection in SLAM. The current approach to place recognition is based on RGB images, but there are relatively few place recognition studies using a point cloud. This study presents the place recognition method based on the surface graph. The proposed method clusters the surfaces in the point cloud and recognizes a place through a surface descriptor...
Human body shapes are considered important information for fashion and clothing companies. In order to design better fitting clothes for the population or target customers, accurate analysis of body shapes is required. So far, most works on grouping body shapes are done using body measurements and classifying them into a given number of clusters. However, with the advancement in 3D body scanning technology,...
3D objects learning is a challenging problem in computer vision and digital multimedia due to the wide development of 3D objects scanning technology. Nevertheless, using machine learning for solving such problems is a potential and effective tool. In this paper, we propose a novel approach for 3D objects labeling, it relies on a multi-class boosting algorithm to train the labeling function and spectral...
In this study we analyzed a series of LiDAR point clouds acquired over Taijiang district (part of Fujian province, China). The objective was to detect and extract water surface area from individual LiDAR point cloud, in a parallel means. To this end, interactive visualization of fine-grained data, global cluster algorithms, and statistical investigation were applied. We first rasterized point clouds...
Finding an object in a 3D scene is an important problem in the robotics, especially in assistive systems for visually impaired people. In most systems, the first and most important step is how to detect an object in a complex environment. In this paper, we propose a method for finding an object using geometrical constraints on depth images from a Kinect. The main advantage of the approach is it is...
In recent years, special interest has been paid to the solution of sector design problem. The airspace is partitioned into sectors, each of them being controlled by a group of controllers. Airspace sectors should be designed cautiously, ensuring that no sector would be overloaded during the day. The objective of an airspace design process is to adapt the airspace according to the evolution of the...
This paper focuses on detecting and classifying pole-like objects from point clouds obtained in urban areas. To achieve our goal, we propose a system consisting of three stages: localization, segmentation and classification. The localization algorithm based on slicing, clustering, pole seed generation and bucket augmentation takes advantage of the unique characteristics of pole-like objects and avoids...
This paper presents an implementation of face recognition, which is a very important task of identifying human faces. Representation of a face image is dealing with keypoints clustering and curve matching approach. In our work we implement the methods for recognition of a 3-D face image with missing and occluded part. The solutions for this problem is found out with the help of SIFT and RANSAC algorithms...
Measuring the geometric structural traits of plants, especially the shape of leaves, plays an important role in the agricultural science. However, most existing techniques and systems have limited overall performance in accuracy, efficiency and descriptive ability, which is insufficient for the requirements in many real applications. In this study, a new kind of sensing device, the Kinect depth sensor...
The intent of 3D-model classification is to find categories of similar objects according to their shapes. This task is a challenging and important problem in 3D-mining and shape processing. In this paper, we present a novel method to categorize 3D-objects based on view-based descriptors. The proposed method goes into two stages. The first stage corresponds to the training in which 3D-objects in the...
In this paper, we propose an original solution to the problem of point cloud clustering. The proposed technique is based on a d-dimensional formulated Delaunay Triangulation (DT) construction algorithm and adapts it to the problem of cluster detection. The introduced algorithm allows this detection as along with the DT construction. Precisely, a criterion that detects occurrences of gaps in the simplex...
In the 3D facial animation and synthesis community, input faces are usually required to be labeled by a set of landmarks for parameterization. Because of the variations in pose, expression and resolution, automatic 3D face landmark localization remains a challenge. In this paper, a novel landmark localization approach is presented. The approach is based on local coordinate coding (LCC) and consists...
Co-segmentation of 3D shapes has been receiving increasing attention, and treated as clustering problem in a descriptor space by a few unsupervised approaches to achieve proper co-segmentation of shapes with large variability. However, most of the existing algorithms are performed on segment level and heavily dependent on the per-object segmentation. Accordingly, we propose a co-segmentation method...
Mitochondria play an important role in cellular physiology and synaptic function. Recent electron microscopy (EM) advances make it possible to observe mitochondrial structure on nanoscale, but the attendant massive EM data unfortunately requires months of tedious manual labor. In this paper, we present an automatic approach for the 3D reconstruction of mitochondria from anisotropic EM stack. We first...
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