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The paper presents a new model for single channel images low-level interpretation. The image is decomposed into a graph which captures a complete set of structural features. The description allows to accurately identify every edge location…

Computer Vision and Pattern Recognition · Computer Science 2019-04-23 Alessandro Dal Palu'

This paper considers non-smooth optimization problems where we seek to minimize the pointwise maximum of a continuously parameterized family of functions. Since the objective function is given as the solution to a maximization problem,…

Optimization and Control · Mathematics 2026-01-12 Dimitris Boskos , Jorge Cortés , Sonia Martínez

Graph sampling is a technique to pick a subset of vertices and/ or edges from original graph. It has a wide spectrum of applications, e.g. survey hidden population in sociology [54], visualize social graph [29], scale down Internet AS graph…

Social and Information Networks · Computer Science 2013-08-28 Pili Hu , Wing Cheong Lau

This paper considers how to separate text and/or graphics from smooth background in screen content and mixed content images and proposes an algorithm to perform this segmentation task. The proposed methods make use of the fact that the…

Computer Vision and Pattern Recognition · Computer Science 2017-12-05 Shervin Minaee , Yao Wang

Staircases are some of the most common building structures in urban environments. Stair detection is an important task for various applications, including the environmental perception of exoskeleton robots, humanoid robots, and rescue…

Computer Vision and Pattern Recognition · Computer Science 2022-02-07 Chen Wang , Zhongcai Pei , Shuang Qiu , Zhiyong Tang

We present a rectangle-based segmentation algorithm that sets up a graph and performs a graph cut to separate an object from the background. However, graph-based algorithms distribute the graph's nodes uniformly and equidistantly on the…

Computer Vision and Pattern Recognition · Computer Science 2012-03-14 Jan Egger , Tina Kapur , Thomas Dukatz , Malgorzata Kolodziej , Dzenan Zukic , Bernd Freisleben , Christopher Nimsky

In the machine learning field, dimensionality reduction is an important task. It mitigates the undesired properties of high-dimensional spaces to facilitate classification, compression, and visualization of high-dimensional data. During the…

Machine Learning · Computer Science 2019-11-19 Mohammed Elhenawy , Mahmoud Masoud , Sebastian Glaser , Andry Rakotonirainy

Augmented reality applications are beginning to change the way sports are broadcast, providing richer experiences and valuable insights to fans. The first step of augmented reality systems is camera calibration, possibly based on detecting…

Computer Vision and Pattern Recognition · Computer Science 2022-08-05 Daniel Berjón , Carlos Cuevas , Narciso García

Given a grid terrain T and a viewpoint v, the viewshed of v is the set of grid points of T that are visible from v. To decide whether a point p is visible one needs to interpolate the elevation of the terrain along the line-of-sight vp.…

Data Structures and Algorithms · Computer Science 2018-10-05 Herman Haverkort , Laura Toma

Much recent attention has been devoted to gradient descent algorithms where the steepest descent step size is replaced by a similar one from a previous iteration or gets updated only once every second step, thus forming a {\em faster…

Computer Vision and Pattern Recognition · Computer Science 2013-08-13 Hui Huang , Uri Ascher

Given the necessity of connecting the unconnected, covering blind spots has emerged as a critical task in the next-generation wireless communication network. A direct solution involves obtaining a coverage manifold that visually showcases…

Networking and Internet Architecture · Computer Science 2023-12-12 Ruibo Wang , Washim Uddin Mondal , Mustafa A. Kishk , Vaneet Aggarwal , Mohamed-Slim Alouini

Shape recognition is the main challenging problem in computer vision. Different approaches and tools are used to solve this problem. Most existing approaches to object recognition are based on pixels. Pixel-based methods are dependent on…

Computer Vision and Pattern Recognition · Computer Science 2019-09-10 Narges Mirehi , Maryam Tahmasbi , Alireza Tavakoli Targhi

Visual grouping is a key mechanism in human scene perception. There, it belongs to the subconscious, early processing and is key prerequisite for other high level tasks such as recognition. In this paper, we introduce an efficient, realtime…

Computer Vision and Pattern Recognition · Computer Science 2016-09-23 Dominik Alexander Klein , Dirk Schulz , Armin Bernd Cremers

Development of the new methods of surface water observation is crucial in the perspective of increasingly frequent extreme hydrological events related to global warming and increasing demand for water. Orthophotos and digital surface models…

Neural and Evolutionary Computing · Computer Science 2022-12-06 Radosław Szostak , Marcin Pietroń , Mirosław Zimnoch , Przemysław Wachniew , Paweł Ćwiąkała , Edyta Puniach

Contour detection has been a fundamental component in many image segmentation and object detection systems. Most previous work utilizes low-level features such as texture or saliency to detect contours and then use them as cues for a…

Computer Vision and Pattern Recognition · Computer Science 2015-04-24 Gedas Bertasius , Jianbo Shi , Lorenzo Torresani

The problem of inferring unknown graph edges from numerical data at a graph's nodes appears in many forms across machine learning. We study a version of this problem that arises in the field of \emph{landscape genetics}, where genetic…

Machine Learning · Computer Science 2021-03-11 Prathamesh Dharangutte , Christopher Musco

Wasserstein gradient flows are continuous time dynamics that define curves of steepest descent to minimize an objective function over the space of probability measures (i.e., the Wasserstein space). This objective is typically a divergence…

Optimization and Control · Mathematics 2021-02-23 Adil Salim , Anna Korba , Giulia Luise

It is a critical issue to compute the shortest paths between nodes in networks. Exact algorithms for shortest paths are usually inapplicable for large scale networks due to the high computational complexity. In this paper, we propose a…

Social and Information Networks · Computer Science 2015-06-29 Shi-nan Gong , Duan-bing Chen , Hui Gao , Guan-nan Wang , Liang-wei Wang

Weakly-supervised semantic segmentation under image tags supervision is a challenging task as it directly associates high-level semantic to low-level appearance. To bridge this gap, in this paper, we propose an iterative bottom-up and…

Computer Vision and Pattern Recognition · Computer Science 2018-06-13 Xiang Wang , Shaodi You , Xi Li , Huimin Ma

Visual scene decomposition into semantic entities is one of the major challenges when creating a reliable object grasping system. Recently, we introduced a bottom-up hierarchical clustering approach which is able to segment objects and…

Computer Vision and Pattern Recognition · Computer Science 2017-01-18 Dominik Alexander Klein , Boris Illing , Bastian Gaspers , Dirk Schulz , Armin Bernd Cremers