Matching Algorithm of 3D Point Clouds Based on Multiscale Features and Covariance Matrix Descriptors
نویسندگان
چکیده
منابع مشابه
Learning Image Descriptors for Matching Based on Haar Features
This paper presents a new and fast binary descriptor for image matching learned from Haar features. The training uses AdaBoost; the weak learner is built on response function for Haar features, instead of histogram-type features. The weak classifier is selected from a large weak feature pool. The selected features have different feature type, scale and position within the patch, having correspo...
متن کاملGlobal Registration of 3D LiDAR Point Clouds Based on Scene Features: Application to Structured Environments
Acquiring 3D data with LiDAR systems involves scanning multiple scenes from different points of view. In actual systems, the ICP algorithm (Iterative Closest Point) is commonly used to register the acquired point clouds together to form a unique one. However, this method faces local minima issues and often needs a coarse initial alignment to converge to the optimum. This paper develops a new me...
متن کاملRetrieving Matching CAD Models by Using Partial 3D Point Clouds
The ability to search for a CAD model that represents a specific physical part is a useful capability that can be used in many different applications. This paper presents an approach to use partial 3D point cloud of an artifact for retrieving the CAD model of the artifact. We assume that the information about the physical parts will be captured by a single 3D scan that produces dense point clou...
متن کاملAn Iterative Closest Points Algorithm for Registration of 3D Laser Scanner Point Clouds with Geometric Features
The Iterative Closest Points (ICP) algorithm is the mainstream algorithm used in the process of accurate registration of 3D point cloud data. The algorithm requires a proper initial value and the approximate registration of two point clouds to prevent the algorithm from falling into local extremes, but in the actual point cloud matching process, it is difficult to ensure compliance with this re...
متن کامل3D Saliency Based on Supervoxels Rarity in Point Clouds
Visual saliency is a computational process that seeks to identify the most attention-drawing regions from a visual point of view. Most methods of salience are based on characteristics such as color, texture and more recently tried to introduce the depth information, which is known to be an important cue in the human cognitive system. We present a new full 3D mechanism of computational attention...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2943003