Computer vision based planogram compliance evaluation

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dc.contributor Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta fi
dc.contributor University of Helsinki, Faculty of Science en
dc.contributor Helsingfors universitet, Matematisk-naturvetenskapliga fakulteten sv
dc.contributor.author Laitala, Julius
dc.date.issued 2021
dc.identifier.uri URN:NBN:fi:hulib-202106092585
dc.identifier.uri http://hdl.handle.net/10138/330784
dc.description.abstract Arranging products in stores according to planograms, optimized product arrangement maps, is important for keeping up with the highly competitive modern retail market. The planograms are realized into product arrangements by humans, a process which is prone to mistakes. Therefore, for optimal merchandising performance, the planogram compliance of the arrangements needs to be evaluated from time to time. We investigate utilizing a computer vision problem setting – retail product detection – to automate planogram compliance evaluation. We introduce the relevant problems, the state-of- the-art approaches for solving them and background information necessary for understanding them. We then propose a computer vision based planogram compliance evaluation pipeline based on the current state of the art. We build our proposed models and algorithms using PyTorch, and run tests against public datasets and an internal dataset collected from a large Nordic retailer. We find that while the retail product detection performance of our proposed approach is quite good, the planogram compliance evaluation performance of our whole pipeline leaves a lot of room for improvement. Still, our approach seems promising, and we propose multiple ways for improving the performance enough to enable possible real world utility. The code used for our experiments and the weights for our models are available at https://github.com/laitalaj/cvpce en
dc.language.iso eng
dc.publisher Helsingin yliopisto fi
dc.publisher University of Helsinki en
dc.publisher Helsingfors universitet sv
dc.subject computer vision
dc.subject object detection
dc.subject retail product detection
dc.subject planogram compliance
dc.title Computer vision based planogram compliance evaluation en
dc.type.ontasot pro gradu -tutkielmat fi
dc.type.ontasot master's thesis en
dc.type.ontasot pro gradu-avhandlingar sv
dct.identifier.urn URN:NBN:fi:hulib-202106092585
dc.subject.specialization Algoritmit fi
dc.subject.specialization Algorithms en
dc.subject.specialization Algoritmer sv
dc.subject.degreeprogram Tietojenkäsittelytieteen maisteriohjelma fi
dc.subject.degreeprogram Master's Programme in Computer Science en
dc.subject.degreeprogram Magisterprogrammet i datavetenskap sv

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