Testing computer vision applications an experience report on introducing code coverage analysis in the field

Iulia Nica, Franz Wotawa, Gerhard Jakob, Kathrin Juhart

Research output: Contribution to conferencePaperpeer-review

Abstract

In this paper we present our work in progress in defining a suitable testing and validation methodology to be used within computer vision (CV) projects. Typical quality assurance (QA) measures, targeting the applicability in real-world scenarios, are meant here to complement the research on specific computer vision methods. While inspecting the existing literature in the domain of CV performance evaluation, we first identified the main challenges the CV researchers have to deal with. Second, as every vision algorithm eventually takes the form of a software program, we followed the classic software development process and performed an in depth code coverage analysis in order to assure the quality of our test suites and pinpoint code areas that need to be reviewed. This further leaves us with the questions of which test coverage tool to prefer in our situation and whether we can introduce some specific evaluation criteria for identifying the right tool to be used within a CV project. In this article we also contribute to answering these questions.

Original languageEnglish
Pages15-21
Number of pages7
Publication statusPublished - 2016
EventJoint International Workshop on Quality Assurance in Computer Vision and the International Workshop on Digital Eco-Systems, - TU Graz, Graz, Austria
Duration: 18 Oct 201119 Jan 2017

Workshop

WorkshopJoint International Workshop on Quality Assurance in Computer Vision and the International Workshop on Digital Eco-Systems,
Country/TerritoryAustria
CityGraz
Period18/10/1119/01/17

ASJC Scopus subject areas

  • Computer Science(all)

Fields of Expertise

  • Information, Communication & Computing

Treatment code (Nähere Zuordnung)

  • Application

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