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This paper presents new methodology for computationally efficient kernel density estimation. It is shown that a large class of kernels allows for exact evaluation of the density estimates using simple recursions. The same methodology can be…

Computation · Statistics 2019-11-12 David P. Hofmeyr

Uncertainty is prevalent in robotics. Due to measurement noise and complex dynamics, we cannot estimate the exact system and environment state. Since conservative motion planners are not guaranteed to find a safe control strategy in a…

Robotics · Computer Science 2023-09-22 Laura Lützow , Yue Meng , Andres Chavez Armijos , Chuchu Fan

The cosmic web is one of the most striking features of the distribution of galaxies and dark matter on the largest scales in the Universe. It is composed of dense regions packed full of galaxies, long filamentary bridges, flattened sheets…

The onset of star formation is set by the collapse of filaments in the interstellar medium. From a theoretical point of view, an isolated cylindrical filament forms cores via the edge effect. Due to the self-gravity of a filament, the…

Astrophysics of Galaxies · Physics 2023-09-08 Elena Hoemann , Stefan Heigl , Andreas Burkert

This article proposes a new path planning method for addressing multi-level terrain situations. The proposed method includes innovations in three aspects: 1) the pre-processing of point cloud maps with a multi-level skip-list structure and…

Robotics · Computer Science 2025-05-01 Yujie Tang , Quan Li , Hao Geng , Yangmin Xie , Hang Shi , Yusheng Yang

The question of how best to estimate a continuous probability density from finite data is an intriguing open problem at the interface of statistics and physics. Previous work has argued that this problem can be addressed in a natural way…

Data Analysis, Statistics and Probability · Physics 2014-07-16 Justin B. Kinney

The characterization of the internal structure of the superclusters of galaxies (walls, filaments and knots where the clusters are located) is paramount for understanding the formation of the Large Scale Structure and for outlining the…

Accurate rail location is a crucial part in the railway support driving system for safety monitoring. LiDAR can obtain point clouds that carry 3D information for the railway environment, especially in darkness and terrible weather…

Computer Vision and Pattern Recognition · Computer Science 2022-08-10 Xinyi Yu , Weiqi He , Xuecheng Qian , Yang Yang , Linlin Ou

Context. Gravitational collapse theory and numerical simulations suggest that the velocity field within large-scale galaxy filaments is dominated by motions along the filaments. Aims. Our aim is to check whether observational data reveal…

Cosmology and Nongalactic Astrophysics · Physics 2015-03-25 Elmo Tempel , Antti Tamm

Context: Star formation takes place in giant molecular clouds, resulting in mass-segregated young stellar clusters composed of Sun-like stars, brown dwarves, and massive O-type(50-100\msun) stars. Aims: To identify candidate hub-filament…

Astrophysics of Galaxies · Physics 2020-10-14 M. S. N. Kumar , P. Palmeirim , D. Arzoumanian , S. I. Inutsuka

In this paper, we propose a method to segment regions in three-dimensional point clouds. We assume that (i) the shape and the number of regions in the point cloud are not known and (ii) the point cloud may be noisy. The method consists of…

Computer Vision and Pattern Recognition · Computer Science 2019-12-02 Matthias Sonntag , Veniamin I. Morgenshtern

Initializing optical flow field by either sparse descriptor matching or dense patch matches has been proved to be particularly useful for capturing large displacements. In this paper, we present a pyramidal gradient matching approach that…

Computer Vision and Pattern Recognition · Computer Science 2017-04-12 Yuanwei Li

We have carried out a search for filamentary structures in the Taurus molecular cloud using $\rm^{13}CO$ line emission data from the FCRAO survey of $\rm \sim100 \, deg^2$. We have used the topological analysis tool, DisPerSe, and…

Solar and Stellar Astrophysics · Physics 2016-02-04 G. V. Panopoulou , K. Tassis , P. F. Goldsmith , M. H. Heyer

In recent years new application areas have emerged in which one aims to capture the geometry of objects by means of three-dimensional point clouds. Often the obtained data consist of a dense sampling of the object's surface, containing many…

Numerical Analysis · Mathematics 2019-10-01 Daniel Tenbrinck , Fjedor Gaede , Martin Burger

The identification of peaks or maxima in probability densities, by mode testing or bump hunting, has become an important problem in applied fields. This task has been approached in the statistical literature from different perspectives,…

Methodology · Statistics 2020-09-01 Jose Ameijeiras-Alonso , Rosa M. Crujeiras , Alberto Rodríguez-Casal

Diffusion models form an important class of generative models today, accounting for much of the state of the art in cutting edge AI research. While numerous extensions beyond image and video generation exist, few of such approaches address…

Machine Learning · Computer Science 2025-04-30 Hao Luan , See-Kiong Ng , Chun Kai Ling

Filamentary structure is important for the ISM and star formation. Galactic distribution of filaments may regulate the star formation rate in the Milky Way. However, interstellar filaments are intrinsically complex, making it difficult to…

Astrophysics of Galaxies · Physics 2024-06-12 Ke Wang , Yifei Ge , Tapas Baug

Pavement cracks is one of the most important reasons that affects the road capacity. Nowadays, China has the longest highway mileage in the world, thus using traditional manual methods to detect pavement cracks is both time and labor…

Image and Video Processing · Electrical Eng. & Systems 2018-06-07 Meng Wang

Object pose estimation from a single view remains a challenging problem. In particular, partial observability, occlusions, and object symmetries eventually result in pose ambiguity. To account for this multimodality, this work proposes…

Computer Vision and Pattern Recognition · Computer Science 2024-12-03 Christian Möller , Niklas Funk , Jan Peters

The amount of collected data in many scientific fields is increasing, all of them requiring a common task: extract knowledge from massive, multi parametric data sets, as rapidly and efficiently possible. This is especially true in astronomy…