Development of an approach for automatic ski jump style scoring

Dejan Štepec (2017) Development of an approach for automatic ski jump style scoring. MSc thesis.

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Abstract

Ski jumping has always been a very popular sport in Slovenia, mostly due to success of our sportsmen. The goal of of this master’s thesis is to develop a method for automatic ski jump scoring from videos. As our main source of information we use locations of human body parts along with skis to capture a full body movement of the entire ski jump. We have used an existing method for human pose estimation from images on the domain of ski jumping with the help of specially built dataset. We extend the method for human pose estimation with the support for ski parts detection. Combined locations of human body parts and ski parts represents an input for the method that performs scoring of the ski jump style. The approach is based on convolutional neural networks that are atypically used on a time series data. Our method is able to operate with an error omparable to real judges.

Item Type:

Thesis (MSc thesis)

Keywords:

ski jumping, ski jumpestimation scoring, convolutional neural networks, human pose estimation

Number of Pages:

Language of Content:

Slovenian

Mentor / Comentors:

Name and Surname	ID	Function
izr. prof. dr. Danijel Skočaj	296	Mentor

Link to COBISS:

http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1537595075)

Institution:

University of Ljubljana

Department:

Faculty of Computer and Information Science

Item ID:

4002

Date Deposited:

14 Oct 2017 10:05

Last Modified:

16 Oct 2017 08:33

URI:

http://eprints.fri.uni-lj.si/id/eprint/4002

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