An In-depth Study of Sparse Codes on Abnormality Detection

Huamin Ren, Hong Pan, Søren Ingvor Olsen, Morten Bornø Jensen, Thomas B. Moeslund

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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302 Downloads (Pure)

Resumé

Sparse representation has been applied successfully in
abnormal event detection, in which the baseline is to learn
a dictionary accompanied by sparse codes. While much
emphasis is put on discriminative dictionary construction,
there are no comparative studies of sparse codes regarding abnormality detection. We present an in-depth study of
two types of sparse codes solutions - greedy algorithms and
convex L1-norm solutions - and their impact on abnormal-
ity detection performance. We also propose our framework
of combining sparse codes with different detection methods.
Our comparative experiments are carried out from various angles to better understand the applicability of sparse
codes, including computation time, reconstruction error,
sparsity, detection accuracy, and their performance combining various detection methods. The experiment results
show that combining OMP codes with maximum coordinate
detection could achieve state-of-the-art performance on the
UCSD dataset [14].
OriginalsprogEngelsk
TitelIEEE Advanced Video and Signal-based Surveillance (AVSS) 2016
Antal sider7
ForlagIEEE
Publikationsdato2016
Sider1-7
ISBN (Trykt)978-1-5090-3812-1
ISBN (Elektronisk)978-1-5090-3811-4
DOI
StatusUdgivet - 2016
BegivenhedThe 13th International Conference on Advanced Video and Signal-Based Surveillance - Colorado Springs, USA
Varighed: 23 aug. 201626 aug. 2016
Konferencens nummer: 13
http://avss2016.org/

Konference

KonferenceThe 13th International Conference on Advanced Video and Signal-Based Surveillance
Nummer13
LandUSA
By Colorado Springs
Periode23/08/201626/08/2016
Internetadresse

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Glossaries
Error detection
Experiments

Citer dette

Ren, H., Pan, H., Olsen, S. I., Jensen, M. B., & Moeslund, T. B. (2016). An In-depth Study of Sparse Codes on Abnormality Detection. I IEEE Advanced Video and Signal-based Surveillance (AVSS) 2016 (s. 1-7). IEEE. https://doi.org/10.1109/AVSS.2016.7738016
Ren, Huamin ; Pan, Hong ; Olsen, Søren Ingvor ; Jensen, Morten Bornø ; Moeslund, Thomas B. / An In-depth Study of Sparse Codes on Abnormality Detection. IEEE Advanced Video and Signal-based Surveillance (AVSS) 2016. IEEE, 2016. s. 1-7
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title = "An In-depth Study of Sparse Codes on Abnormality Detection",
abstract = "Sparse representation has been applied successfully inabnormal event detection, in which the baseline is to learna dictionary accompanied by sparse codes. While muchemphasis is put on discriminative dictionary construction,there are no comparative studies of sparse codes regarding abnormality detection. We present an in-depth study oftwo types of sparse codes solutions - greedy algorithms andconvex L1-norm solutions - and their impact on abnormal-ity detection performance. We also propose our frameworkof combining sparse codes with different detection methods.Our comparative experiments are carried out from various angles to better understand the applicability of sparsecodes, including computation time, reconstruction error,sparsity, detection accuracy, and their performance combining various detection methods. The experiment resultsshow that combining OMP codes with maximum coordinatedetection could achieve state-of-the-art performance on theUCSD dataset [14].",
author = "Huamin Ren and Hong Pan and Olsen, {S{\o}ren Ingvor} and Jensen, {Morten Born{\o}} and Moeslund, {Thomas B.}",
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Ren, H, Pan, H, Olsen, SI, Jensen, MB & Moeslund, TB 2016, An In-depth Study of Sparse Codes on Abnormality Detection. i IEEE Advanced Video and Signal-based Surveillance (AVSS) 2016. IEEE, s. 1-7, The 13th International Conference on Advanced Video and Signal-Based Surveillance, Colorado Springs, USA, 23/08/2016. https://doi.org/10.1109/AVSS.2016.7738016

An In-depth Study of Sparse Codes on Abnormality Detection. / Ren, Huamin; Pan, Hong; Olsen, Søren Ingvor; Jensen, Morten Bornø; Moeslund, Thomas B.

IEEE Advanced Video and Signal-based Surveillance (AVSS) 2016. IEEE, 2016. s. 1-7.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

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Ren H, Pan H, Olsen SI, Jensen MB, Moeslund TB. An In-depth Study of Sparse Codes on Abnormality Detection. I IEEE Advanced Video and Signal-based Surveillance (AVSS) 2016. IEEE. 2016. s. 1-7 https://doi.org/10.1109/AVSS.2016.7738016