Multi Temporal Distance Images for Shot Detection in Soccer Games (bibtex)
by M Hoernig, M Herrmann and B Radig
Abstract:
We present a new approach for video shot detection and introduce multi temporal distance images (MTDIs), formed by chi-square based similarity measures that are calculated pairwise within a floating window of video frames. By using MTDI-based boundary detectors, various cuts and transitions in various shapes (dissolves, overlayed effects, fades, and others) can be determined. The algorithm has been developed within the special context of soccer game TV broadcasts, where a particular interest in long view shots is intrinsic. With a correct shot detection rate in camera 1 shots of 98.2% within our representative test data set, our system outperforms competing state-of-the-art systems.
Reference:
Multi Temporal Distance Images for Shot Detection in Soccer Games (M Hoernig, M Herrmann and B Radig), In EUSIPCO 2014 (22nd European Signal Processing Conference 2014) (EUSIPCO 2014), 2014. 
Bibtex Entry:
@inproceedings{hoernig_shot_detection_2014,
 author = {M Hoernig and M Herrmann and B Radig},
 title = {Multi Temporal Distance Images for Shot Detection in Soccer Games},
 booktitle = {EUSIPCO 2014 (22nd European Signal Processing Conference 2014) (EUSIPCO
	2014)},
 year = {2014},
 address = {Lisbon, Portugal},
 month = {sep},
 abstract = {We present a new approach for video shot detection and introduce multi
	temporal distance images (MTDIs), formed by chi-square based similarity
	measures that are calculated pairwise within a floating window of
	video frames. By using MTDI-based boundary detectors, various cuts
	and transitions in various shapes (dissolves, overlayed effects,
	fades, and others) can be determined. The algorithm has been developed
	within the special context of soccer game TV broadcasts, where a
	particular interest in long view shots is intrinsic. With a correct
	shot detection rate in camera 1 shots of 98.2\% within our representative
	test data set, our system outperforms competing state-of-the-art
	systems.},
 days = {1},
 keywords = {soccer video analysis; video indexing; multi temporal distance image
	(MTDI); video segmentation; video shot boundary detection; soccer},
}
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Multi Temporal Distance Images for Shot Detection in Soccer Games (bibtex)
Multi Temporal Distance Images for Shot Detection in Soccer Games (bibtex)
by M Hoernig, M Herrmann and B Radig
Abstract:
We present a new approach for video shot detection and introduce multi temporal distance images (MTDIs), formed by chi-square based similarity measures that are calculated pairwise within a floating window of video frames. By using MTDI-based boundary detectors, various cuts and transitions in various shapes (dissolves, overlayed effects, fades, and others) can be determined. The algorithm has been developed within the special context of soccer game TV broadcasts, where a particular interest in long view shots is intrinsic. With a correct shot detection rate in camera 1 shots of 98.2% within our representative test data set, our system outperforms competing state-of-the-art systems.
Reference:
Multi Temporal Distance Images for Shot Detection in Soccer Games (M Hoernig, M Herrmann and B Radig), In EUSIPCO 2014 (22nd European Signal Processing Conference 2014) (EUSIPCO 2014), 2014. 
Bibtex Entry:
@inproceedings{hoernig_shot_detection_2014,
 author = {M Hoernig and M Herrmann and B Radig},
 title = {Multi Temporal Distance Images for Shot Detection in Soccer Games},
 booktitle = {EUSIPCO 2014 (22nd European Signal Processing Conference 2014) (EUSIPCO
	2014)},
 year = {2014},
 address = {Lisbon, Portugal},
 month = {sep},
 abstract = {We present a new approach for video shot detection and introduce multi
	temporal distance images (MTDIs), formed by chi-square based similarity
	measures that are calculated pairwise within a floating window of
	video frames. By using MTDI-based boundary detectors, various cuts
	and transitions in various shapes (dissolves, overlayed effects,
	fades, and others) can be determined. The algorithm has been developed
	within the special context of soccer game TV broadcasts, where a
	particular interest in long view shots is intrinsic. With a correct
	shot detection rate in camera 1 shots of 98.2\% within our representative
	test data set, our system outperforms competing state-of-the-art
	systems.},
 days = {1},
 keywords = {soccer video analysis; video indexing; multi temporal distance image
	(MTDI); video segmentation; video shot boundary detection; soccer},
}
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About

I received my diploma degree in computer science with emphasis on artificial intelligence from the Julius-Maximilians-Universität Würzburg in 2007. From 2007 to 2012 I was working as a software engineer for industrial computer vision systems in the private sector. Additionally, I was a research assistant at the Hochschule Rosenheim from 2010 to 2012. Since 2012 I am part of the research group Image Understanding and Knowledge-Based System at the Technische Universität München headed by Bernd Radig. My research interests include computer vision, machine learning, and especially the detection and tracking of objects in videos.

Projects

My work includes the following research projects:

Publications