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An Effective Imaging System for 3D Detection of Occluded Objects

Published: 04 June 2021 Publication History

Abstract

Occluded objects detection is a challenge task in computer vision. To address this problem, this paper proposes an effective light field imaging system for occluded objects 3D detection, which integrates digital refocus methods to imaging occluded objects and deep learning based method to located objects position with defocus clues. Camera arrays based integral imaging system could provide focal stacks images, which makes occluded objects more clear and attenuates foreground occlusion. With observation that recognition probability are related to objects clarity, as well as focal length of images, recognition probability based defocus clues are proposed to located objects depth. Hierarchical object localization process is applied on refocus images stacks to coarsely located object depth by detected probabilities, following gradient based fine-grained defocus response process could further refine the depth accuracy. With the depths from defocus clues and detected locations from neural model, proposed algorithm could achieve 3D object detection under partial occlusion. Furthermore, a parallel computation framework is proposed to accelerate whole detection process. Real experiments show the robust performance of proposed 3D occluded objects detection algorithm.

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Cited By

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  • (2023)Development of a Fuzzy Logic Controller for Autonomous Navigation of Building Inspection Robots in Unknown EnvironmentsJournal of Computing in Civil Engineering10.1061/JCCEE5.CPENG-506037:4Online publication date: Jul-2023
  • (2023)A systematic review of object detection from images using deep learningMultimedia Tools and Applications10.1007/s11042-023-15981-y83:4(12253-12338)Online publication date: 24-Jun-2023

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cover image ACM Other conferences
ICIGP '21: Proceedings of the 2021 4th International Conference on Image and Graphics Processing
January 2021
231 pages
ISBN:9781450389105
DOI:10.1145/3447587
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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 June 2021

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Author Tags

  1. 3D detection
  2. Computational photography
  3. Deep Learning
  4. Light Field

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  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • Shanghai Rising Stars of Medical Talent Youth Development Program
  • Youth Program of Zhejiang Provincial Natural Science Foundation of China
  • Shanghai Jiao Tong University Biomedical Engineering Cross Research Foundation
  • National Key Research Development Program of China
  • National Natural Science Fund of China

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ICIGP 2021

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Cited By

View all
  • (2023)Development of a Fuzzy Logic Controller for Autonomous Navigation of Building Inspection Robots in Unknown EnvironmentsJournal of Computing in Civil Engineering10.1061/JCCEE5.CPENG-506037:4Online publication date: Jul-2023
  • (2023)A systematic review of object detection from images using deep learningMultimedia Tools and Applications10.1007/s11042-023-15981-y83:4(12253-12338)Online publication date: 24-Jun-2023

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