Preventing Drowning Accidents Using Thermal Cameras

Søren Bonderup; Jonas Lundgaard Olsson; Morten Bojesen Bonderup; Thomas B. Moeslund

doi:10.1007/978-3-319-50832-0_12

Preventing Drowning Accidents Using Thermal Cameras

Søren Bonderup, Jonas Lundgaard Olsson, Morten Bojesen Bonderup, Thomas B. Moeslund

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

3 Citations (Scopus)

Abstract

Every year approximately 372 000 people die from unintentional drowning, causing it to be a top-3 cause to unintentional injury [1]. In Denmark 25% of drownings happen at harbor areas [2]. To address this problem thermal cameras have been placed strategically at a harbor. Using computer vision techniques an automatic surveillance system for predicting and detecting drowning accidents has been implemented. First a person detector has been implemented using simple human characteristics. The person is tracked using a Kalman Filter. Using the tracker as a prior, a fall prediction is determined. A fall detector is implemented using a virtual trip-wire in combination with an optical flow algorithm making the system able to detect 100% of all falls and only yielding a 0.08 false positive rate hourly. The entire system has been developed using 155 h of real life thermal video, hereof 56 h are manually annotated.

Original language	English
Title of host publication	Advances in Visual Computing
Editors	George Bebis, Richard Boyle, Bahram Parvin, Darco Koracin, Faith Porikili, Sandra Skaff, Alireza Entezari, Jianjuan Min, Daisuke Iwai, Amela Sadagic, Carlos Scheidegger, Tobias Isenberg
Number of pages	12
Publisher	Springer
Publication date	2016
Pages	111-122
ISBN (Print)	978-3-319-50831-3
ISBN (Electronic)	978-3-319-50832-0
DOIs	https://doi.org/10.1007/978-3-319-50832-0_12
Publication status	Published - 2016
Event	ISVC16: 12th International Symposium on Visual Computing - Monte Carlo Resort & Casino, Las Vegas, United States Duration: 12 Dec 2016 → 14 Dec 2016 http://www.isvc.net

Conference

Conference	ISVC16: 12th International Symposium on Visual Computing
Location	Monte Carlo Resort & Casino
Country/Territory	United States
City	Las Vegas
Period	12/12/2016 → 14/12/2016
Internet address	http://www.isvc.net

Series	Lecture Notes in Computer Science
Volume	10073
ISSN	0302-9743

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Bonderup, S., Olsson, J. L., Bonderup, M. B., & Moeslund, T. B. (2016). Preventing Drowning Accidents Using Thermal Cameras. In G. Bebis, R. Boyle, B. Parvin, D. Koracin, F. Porikili, S. Skaff, A. Entezari, J. Min, D. Iwai, A. Sadagic, C. Scheidegger, & T. Isenberg (Eds.), Advances in Visual Computing (pp. 111-122). Springer. https://doi.org/10.1007/978-3-319-50832-0_12

Bonderup, Søren ; Olsson, Jonas Lundgaard ; Bonderup, Morten Bojesen et al. / Preventing Drowning Accidents Using Thermal Cameras. Advances in Visual Computing. editor / George Bebis ; Richard Boyle ; Bahram Parvin ; Darco Koracin ; Faith Porikili ; Sandra Skaff ; Alireza Entezari ; Jianjuan Min ; Daisuke Iwai ; Amela Sadagic ; Carlos Scheidegger ; Tobias Isenberg. Springer, 2016. pp. 111-122 (Lecture Notes in Computer Science, Vol. 10073).

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title = "Preventing Drowning Accidents Using Thermal Cameras",

abstract = "Every year approximately 372 000 people die from unintentional drowning, causing it to be a top-3 cause to unintentional injury [1]. In Denmark 25% of drownings happen at harbor areas [2]. To address this problem thermal cameras have been placed strategically at a harbor. Using computer vision techniques an automatic surveillance system for predicting and detecting drowning accidents has been implemented. First a person detector has been implemented using simple human characteristics. The person is tracked using a Kalman Filter. Using the tracker as a prior, a fall prediction is determined. A fall detector is implemented using a virtual trip-wire in combination with an optical flow algorithm making the system able to detect 100% of all falls and only yielding a 0.08 false positive rate hourly. The entire system has been developed using 155 h of real life thermal video, hereof 56 h are manually annotated.",

author = "S{\o}ren Bonderup and Olsson, {Jonas Lundgaard} and Bonderup, {Morten Bojesen} and Moeslund, {Thomas B.}",

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editor = "George Bebis and Richard Boyle and Bahram Parvin and Darco Koracin and Faith Porikili and Sandra Skaff and Alireza Entezari and Jianjuan Min and Daisuke Iwai and Amela Sadagic and Carlos Scheidegger and Tobias Isenberg",

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Bonderup, S, Olsson, JL, Bonderup, MB & Moeslund, TB 2016, Preventing Drowning Accidents Using Thermal Cameras. in G Bebis, R Boyle, B Parvin, D Koracin, F Porikili, S Skaff, A Entezari, J Min, D Iwai, A Sadagic, C Scheidegger & T Isenberg (eds), Advances in Visual Computing. Springer, Lecture Notes in Computer Science, vol. 10073, pp. 111-122, ISVC16: 12th International Symposium on Visual Computing, Las Vegas, United States, 12/12/2016. https://doi.org/10.1007/978-3-319-50832-0_12

Preventing Drowning Accidents Using Thermal Cameras. / Bonderup, Søren; Olsson, Jonas Lundgaard; Bonderup, Morten Bojesen et al.
Advances in Visual Computing. ed. / George Bebis; Richard Boyle; Bahram Parvin; Darco Koracin; Faith Porikili; Sandra Skaff; Alireza Entezari; Jianjuan Min; Daisuke Iwai; Amela Sadagic; Carlos Scheidegger; Tobias Isenberg. Springer, 2016. p. 111-122 (Lecture Notes in Computer Science, Vol. 10073).

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Preventing Drowning Accidents Using Thermal Cameras

AU - Bonderup, Søren

AU - Olsson, Jonas Lundgaard

AU - Bonderup, Morten Bojesen

AU - Moeslund, Thomas B.

PY - 2016

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N2 - Every year approximately 372 000 people die from unintentional drowning, causing it to be a top-3 cause to unintentional injury [1]. In Denmark 25% of drownings happen at harbor areas [2]. To address this problem thermal cameras have been placed strategically at a harbor. Using computer vision techniques an automatic surveillance system for predicting and detecting drowning accidents has been implemented. First a person detector has been implemented using simple human characteristics. The person is tracked using a Kalman Filter. Using the tracker as a prior, a fall prediction is determined. A fall detector is implemented using a virtual trip-wire in combination with an optical flow algorithm making the system able to detect 100% of all falls and only yielding a 0.08 false positive rate hourly. The entire system has been developed using 155 h of real life thermal video, hereof 56 h are manually annotated.

AB - Every year approximately 372 000 people die from unintentional drowning, causing it to be a top-3 cause to unintentional injury [1]. In Denmark 25% of drownings happen at harbor areas [2]. To address this problem thermal cameras have been placed strategically at a harbor. Using computer vision techniques an automatic surveillance system for predicting and detecting drowning accidents has been implemented. First a person detector has been implemented using simple human characteristics. The person is tracked using a Kalman Filter. Using the tracker as a prior, a fall prediction is determined. A fall detector is implemented using a virtual trip-wire in combination with an optical flow algorithm making the system able to detect 100% of all falls and only yielding a 0.08 false positive rate hourly. The entire system has been developed using 155 h of real life thermal video, hereof 56 h are manually annotated.

U2 - 10.1007/978-3-319-50832-0_12

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EP - 122

BT - Advances in Visual Computing

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A2 - Parvin, Bahram

A2 - Koracin, Darco

A2 - Porikili, Faith

A2 - Skaff, Sandra

A2 - Entezari, Alireza

A2 - Min, Jianjuan

A2 - Iwai, Daisuke

A2 - Sadagic, Amela

A2 - Scheidegger, Carlos

A2 - Isenberg, Tobias

PB - Springer

T2 - ISVC16: 12th International Symposium on Visual Computing

Y2 - 12 December 2016 through 14 December 2016

ER -

Bonderup S, Olsson JL, Bonderup MB, Moeslund TB. Preventing Drowning Accidents Using Thermal Cameras. In Bebis G, Boyle R, Parvin B, Koracin D, Porikili F, Skaff S, Entezari A, Min J, Iwai D, Sadagic A, Scheidegger C, Isenberg T, editors, Advances in Visual Computing. Springer. 2016. p. 111-122. (Lecture Notes in Computer Science, Vol. 10073). doi: 10.1007/978-3-319-50832-0_12

Preventing Drowning Accidents Using Thermal Cameras

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