Active Vision System with Human Detection - Using RGB-D images and machine learning algorithms

Publicerad

Typ

Examensarbete för masterexamen
Master Thesis

Modellbyggare

Tidskriftstitel

ISSN

Volymtitel

Utgivare

Sammanfattning

This master's thesis will focus on an active safety system for the protection of humans close to commercial construction equipments. The purpose is therefore to propose sensors and algorithms suitable for human detection and furthermore to demonstrate a proof of concept. Early on in the project it was decided to use RGB-D images, which is a conventional color image together with a depth map. This report analyzes both a Kinect sensor and a stereo vision system in order to generate a depth map. Machine learning algorithms were used to classify humans where an artificial neural network was found to be the best performing classifier. Finding informative features is important to facilitate classification. Several imaging features were tested and the six most interesting are presented in this report. The feature called fourier descriptor showed the best performance.

Beskrivning

Ämne/nyckelord

Signalbehandling, Hållbar utveckling, Produktion, Signal Processing, Sustainable Development, Production

Citation

Arkitekt (konstruktör)

Geografisk plats

Byggnad (typ)

Byggår

Modelltyp

Skala

Teknik / material

Index

item.page.endorsement

item.page.review

item.page.supplemented

item.page.referenced