Resolution-Aware Deep Multi-View Camera Systems

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

1 Scopus citations


Recognizing 3D objects with multiple views is an important problem in computer vision. However, multi view object recognition can be challenging for networked embedded intelligent systems (IoT devices) as they have data transmission limitation as well as computational resource constraint. In this work, we design an enhanced multi-view distributed recognition system which deploys a view importance estimator to transmit data with different resolutions. Moreover, a multi-view learning-based super-resolution enhancer is used at the back-end to compensate for the performance degradation caused by information loss from resolution reduction. The extensive experiments on the benchmark dataset demonstrate that the designed resolution-aware multi-view system can decrease the endpoint's communication energy by a factor of 5× while sustaining accuracy. Further experiments on the enhanced multi-view recognition system show that accuracy increment can be achieved with minimum effect on the computational cost of back-end system.

Original languageEnglish (US)
Title of host publicationProceedings of the 2021 Design, Automation and Test in Europe, DATE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9783981926354
StatePublished - Feb 1 2021
Event2021 Design, Automation and Test in Europe Conference and Exhibition, DATE 2021 - Virtual, Online
Duration: Feb 1 2021Feb 5 2021

Publication series

NameProceedings -Design, Automation and Test in Europe, DATE
ISSN (Print)1530-1591


Conference2021 Design, Automation and Test in Europe Conference and Exhibition, DATE 2021
CityVirtual, Online

All Science Journal Classification (ASJC) codes

  • General Engineering


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