Context-aware collaborative object recognition for distributed multi camera time series data

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent research shows that the multi-view system for object recognition outperforms the single-view point system. When viewpoints are added, additional communication cost and cost to deploy the viewpoints are also added. However, prior work has shown that not all of the views are useful, and poor viewpoints can be excluded. This paper explores the dynamic context application for a Context-Aware Neural Network. The Context-Aware Neural Network uses Shannon entropy value to acquire likelihood, and this likelihood value to reduce viewpoints in a distributed system. However, reducing viewpoints were done on static image recognition, so the spatial relation between the views and subject is fixed. Expansion to dynamic context is essential since most of the real world is a series of images, rather than a snapshot of the scene. Apart from testing on images of 3D CAD data, this paper illustrates the generation of 3D CAD data videos, and examines the video analysis of the generated videos using the Context-Aware Neural Network. In this particular setup, relevant objects move with respect to a fixed set of cameras. It is reported that the viewpoints can be reduced, and context of the trained data matters in the setup.

Original languageEnglish (US)
Title of host publicationProceedings of the 10th International Symposium on Information and Communication Technology, SoICT 2019
PublisherAssociation for Computing Machinery
Pages154-161
Number of pages8
ISBN (Electronic)9781450372459
DOIs
StatePublished - Dec 4 2019
Event10th International Symposium on Information and Communication Technology, SoICT 2019 - Ha Noi and Ha Long, Viet Nam
Duration: Dec 4 2019Dec 6 2019

Publication series

NameACM International Conference Proceeding Series

Conference

Conference10th International Symposium on Information and Communication Technology, SoICT 2019
CountryViet Nam
CityHa Noi and Ha Long
Period12/4/1912/6/19

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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  • Cite this

    Shin, P. W., Sampson, J., & Narayanan, V. (2019). Context-aware collaborative object recognition for distributed multi camera time series data. In Proceedings of the 10th International Symposium on Information and Communication Technology, SoICT 2019 (pp. 154-161). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3368926.3369666