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Adjacency list

About: Adjacency list is a research topic. Over the lifetime, 4419 publications have been published within this topic receiving 78449 citations.


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Journal ArticleDOI
TL;DR: In this article, a computational paradigm called spatial aggregation has been developed to unify the description of a class of imagistic problem solvers (e.g., kam, maps, and hipair).
Abstract: Visual thinking plays an important role in scientific reasoning Based on the research in automating diverse reasoning tasks about dynamical systems, nonlinear controllers, kinematic mechanisms, and fluid motion, we have identified a style of visual thinking, imagistic reasoning Imagistic reasoning organizes computations around image-like, analogue representations so that perceptual and symbolic operations can be brought to bear to infer structure and behavior Programs incorporating imagistic reasoning have been shown to perform at an expert level in domains that defy current analytic or numerical methods We have developed a computational paradigm, spatial aggregation, to unify the description of a class of imagistic problem solvers A program written in this paradigm has the following properties It takes a continuous field and optional objective functions as input, and produces high-level descriptions of structure, behavior, or control actions It computes a multi-layer of intermediate representations, called spatial aggregates, by forming equivalence classes and adjacency relations It employs a small set of generic operators such as aggregation, classification, and localization to perform bidirectional mapping between the information-rich field and successively more abstract spatial aggregates It uses a data structure, the neighborhood graph, as a common interface to modularize computations To illustrate our theory, we describe the computational structure of three implemented problem solvers - kam, maps, and hipair - in terms of the spatial aggregation generic operators by mixing and matching a library of commonly used routines

73 citations

Proceedings Article
01 Jan 2006
TL;DR: Property of point sets are investigated to derive criteria for automatic hole detection and a final boundary loop extraction step uses this probability and exploits additional coherence properties of the boundary to derive a robust and automatic holes detection algorithm.
Abstract: Models of non-trivial objects resulting from a 3d data acquisition process (e.g. Laser Range Scanning) often contain holes due to occlusion, reflectance or transparency. As point set surfaces are unstructured surface representations with no adjacency or connectivity information, defining and detecting holes is a non-trivial task. In this paper we investigate properties of point sets to derive criteria for automatic hole detection. For each point, we combine several criteria into an integrated boundary probability. A final boundary loop extraction step uses this probability and exploits additional coherence properties of the boundary to derive a robust and automatic hole detection algorithm.

73 citations

Journal ArticleDOI
TL;DR: A Monte Carlo integer programming algorithm developed to generate short-term, spatially feasible timber harvest plans for a New Brunswick Crown license indicates that it is suitable for spatially constrained harvest scheduling on Crown licenses in New Brunswick.
Abstract: A Monte Carlo integer programming algorithm was developed to generate short-term (25-year), spatially feasible timber harvest plans for a New Brunswick Crown license. Solutions for the short-term plan are considered feasible if they meet spatial and temporal harvest-flow and adjacency constraints. The solution search procedure integrates a randomly generated harvesting sequence and checks of harvest-flow and adjacency constraints. The model was used to determine the annual allowable cut under three constraint formulations. The three formulations represented increasing levels of adjacency constraints, from no constraints to levels similar to current provincial requirements. The annual allowable cut under the most strict constraint formulation was reduced by 9% from the unconstrained formulation, for a given mapping strategy of a long-term harvest schedule. These applications of the model indicate that it is suitable for spatially constrained harvest scheduling on Crown licenses in New Brunswick.

72 citations

Proceedings ArticleDOI
12 Jul 2020
TL;DR: This is the first paper that reconciles visual-inertial SLAM and dense human mesh tracking and can have a profound impact on planning and decision-making, human-robot interaction, long-term autonomy, and scene prediction.
Abstract: We present a unified representation for actionable spatial perception: 3D Dynamic Scene Graphs. Scene graphs are directed graphs where nodes represent entities in the scene (e.g. objects, walls, rooms), and edges represent relations (e.g. inclusion, adjacency) among nodes. Dynamic scene graphs (DSGs) extend this notion to represent dynamic scenes with moving agents (e.g. humans, robots), and to include actionable information that supports planning and decision-making (e.g. spatio-temporal relations, topology at different levels of abstraction). Our second contribution is to provide the first fully automatic Spatial PerceptIon eNgine(SPIN) to build a DSG from visual-inertial data. We integrate state-of-the-art techniques for object and human detection and pose estimation, and we describe how to robustly infer object, robot, and human nodes in crowded scenes. To the best of our knowledge, this is the first paper that reconciles visual-inertial SLAM and dense human mesh tracking. Moreover, we provide algorithms to obtain hierarchical representations of indoor environments (e.g. places, structures, rooms) and their relations. Our third contribution is to demonstrate the proposed spatial perception engine in a photo-realistic Unity-based simulator, where we assess its robustness and expressiveness. Finally, we discuss the implications of our proposal on modern robotics applications. 3D Dynamic Scene Graphs can have a profound impact on planning and decision-making, human-robot interaction, long-term autonomy, and scene prediction. A video abstract is available at this https URL

72 citations

Journal ArticleDOI
TL;DR: The distance spectrum and energy of the join-based compositions of regular graphs in terms of their adjacency spectrum is described and it is shown that there exist a number of families of sets of noncospectral graphs with equal distance energy.

72 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023209
2022439
2021283
2020280
2019296
2018232