Specifying and Evaluating Quality Metrics for Vision-based Perception Systems

Anand Balakrishnan, Aniruddh G. Puranic, Xin Qin, Adel Dokhanchi, Jyotirmoy V. Deshmukh, Hani Ben Amor, Georgios Fainekos

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

1 Scopus citations

Abstract

Robust perception algorithms are a vital ingredient for autonomous systems such as self-driving vehicles. Checking the correctness of perception algorithms such as those based on deep convolutional neural networks (CNN) is a formidable challenge problem. In this paper, we suggest the use of Timed Quality Temporal Logic (TQTL) as a formal language to express desirable spatio-temporal properties of a perception algorithm processing a video. While perception algorithms are traditionally tested by comparing their performance to ground truth labels, we show how TQTL can be a useful tool to determine quality of perception, and offers an alternative metric that can give useful information, even in the absence of ground truth labels. We demonstrate TQTL monitoring on two popular CNNs: YOLO and SqueezeDet, and give a comparative study of the results obtained for each architecture.

Original languageEnglish (US)
Title of host publicationProceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, DATE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1433-1438
Number of pages6
ISBN (Electronic)9783981926323
DOIs
StatePublished - May 14 2019
Event22nd Design, Automation and Test in Europe Conference and Exhibition, DATE 2019 - Florence, Italy
Duration: Mar 25 2019Mar 29 2019

Publication series

NameProceedings of the 2019 Design, Automation and Test in Europe Conference and Exhibition, DATE 2019

Conference

Conference22nd Design, Automation and Test in Europe Conference and Exhibition, DATE 2019
CountryItaly
CityFlorence
Period3/25/193/29/19

Keywords

  • Autonomous vehicles
  • Image processing
  • Monitoring
  • Perception
  • Quality Metrics
  • Temporal Logic

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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