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Recognizing planar kinematic mechanisms from a single image using evolutionary computation

Published: 12 July 2014 Publication History

Abstract

In this paper, a method is presented that automatically recognizes kinematic mechanisms from textbook images using an evolutionary algorithm to complement computer vision techniques for object detection. Specifically, a nondominated sorting genetic algorithm (NSGA-II) is used to optimize the number and position of mechanical joints in an image and corresponding joint connections (i.e. rigid bodies) such that Pareto front solutions maximize image consistency and mechanical feasibility. A well-known object detector is used as an example method for locating joints, and local image features between pairwise detected joints are used to predict likely connections. The performance of the algorithm using these specific vision techniques is compared to a parameterized detection scheme in order to decouple the efficacy of the object detector from the evolutionary algorithm. Experiments were performed to validate this approach on selected images from a custom dataset, and the results demonstrate reasonable success in both accuracy and speed.

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Cited By

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  • (2023)Transforming Hand-Drawn Sketches of Linkage Mechanisms Into Their Digital RepresentationJournal of Computing and Information Science in Engineering10.1115/1.406403724:1Online publication date: 30-Nov-2023
  • (2023)Automatic Identification of Kinematic Diagrams with Computer VisionProceedings of the XV Ibero-American Congress of Mechanical Engineering10.1007/978-3-031-38563-6_62(425-431)Online publication date: 3-Aug-2023
  • (2018)A Hybrid Decision Model for Heterogeneous Schemes in "Internet Plus" Hackerspace Product Development2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)10.1109/ICEBE.2018.00020(62-69)Online publication date: Oct-2018
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cover image ACM Conferences
GECCO '14: Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation
July 2014
1478 pages
ISBN:9781450326629
DOI:10.1145/2576768
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 12 July 2014

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Author Tags

  1. computer vision
  2. evolutionary multiobjective optimization
  3. kinematic simulation
  4. object recognition

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GECCO '14
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GECCO '14: Genetic and Evolutionary Computation Conference
July 12 - 16, 2014
BC, Vancouver, Canada

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GECCO '14 Paper Acceptance Rate 180 of 544 submissions, 33%;
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

View all
  • (2023)Transforming Hand-Drawn Sketches of Linkage Mechanisms Into Their Digital RepresentationJournal of Computing and Information Science in Engineering10.1115/1.406403724:1Online publication date: 30-Nov-2023
  • (2023)Automatic Identification of Kinematic Diagrams with Computer VisionProceedings of the XV Ibero-American Congress of Mechanical Engineering10.1007/978-3-031-38563-6_62(425-431)Online publication date: 3-Aug-2023
  • (2018)A Hybrid Decision Model for Heterogeneous Schemes in "Internet Plus" Hackerspace Product Development2018 IEEE 15th International Conference on e-Business Engineering (ICEBE)10.1109/ICEBE.2018.00020(62-69)Online publication date: Oct-2018
  • (2018)Intermodal image-based recognition of planar kinematic mechanismsJournal of Visual Languages and Computing10.1016/j.jvlc.2014.10.02427:C(38-48)Online publication date: 27-Dec-2018
  • (2018)Characterizing the performance of an image-based recognizer for planar mechanical linkages in textbook graphics and hand-drawn sketchesComputers and Graphics10.1016/j.cag.2015.06.00252:C(1-17)Online publication date: 23-Dec-2018

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