Thermal vision human classification and localization using bag of visual word

Sourabh Malpani; C. S. Asha; A. V. Narasimhadhan

doi:10.1109/TENCON.2016.7848627

Thermal vision human classification and localization using bag of visual word

Sourabh Malpani
, C. S. Asha
, A. V. Narasimhadhan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

Abstract

Human detection in thermal images has recently gained a lot of attention in computer vision due to its large number of applications. The characteristics of thermal images are poor illumination, low contrast due to capturing devices and poor environment conditions. Human classification and localization are being done using bag of visual word method. Bag of visual word method has been widely used for visible spectrum. In this work, we have extended it to thermal images. A new human detection scheme is present for thermal image using SURF features with Bag of Word. SURF has been compared with different binary feature descriptors. SURF feature descriptor outperforms BRISK and FREAK feature descriptors in terms of accuracy, F-score.

Original language	English
Title of host publication	Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	3135-3139
Number of pages	5
ISBN (Electronic)	9781509025961
DOIs	https://doi.org/10.1109/TENCON.2016.7848627
Publication status	Published - 08-02-2017
Event	2016 IEEE Region 10 Conference, TENCON 2016 - Singapore, Singapore Duration: 22-11-2016 → 25-11-2016

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Conference

Conference	2016 IEEE Region 10 Conference, TENCON 2016
Country/Territory	Singapore
City	Singapore
Period	22-11-16 → 25-11-16

All Science Journal Classification (ASJC) codes

Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/TENCON.2016.7848627

Cite this

Malpani, S., Asha, C. S., & Narasimhadhan, A. V. (2017). Thermal vision human classification and localization using bag of visual word. In Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016 (pp. 3135-3139). Article 7848627 (IEEE Region 10 Annual International Conference, Proceedings/TENCON). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.2016.7848627

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title = "Thermal vision human classification and localization using bag of visual word",

abstract = "Human detection in thermal images has recently gained a lot of attention in computer vision due to its large number of applications. The characteristics of thermal images are poor illumination, low contrast due to capturing devices and poor environment conditions. Human classification and localization are being done using bag of visual word method. Bag of visual word method has been widely used for visible spectrum. In this work, we have extended it to thermal images. A new human detection scheme is present for thermal image using SURF features with Bag of Word. SURF has been compared with different binary feature descriptors. SURF feature descriptor outperforms BRISK and FREAK feature descriptors in terms of accuracy, F-score.",

author = "Sourabh Malpani and Asha, \{C. S.\} and Narasimhadhan, \{A. V.\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Region 10 Conference, TENCON 2016 ; Conference date: 22-11-2016 Through 25-11-2016",

year = "2017",

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doi = "10.1109/TENCON.2016.7848627",

language = "English",

series = "IEEE Region 10 Annual International Conference, Proceedings/TENCON",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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address = "United States",

}

Malpani, S, Asha, CS & Narasimhadhan, AV 2017, Thermal vision human classification and localization using bag of visual word. in Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016., 7848627, IEEE Region 10 Annual International Conference, Proceedings/TENCON, Institute of Electrical and Electronics Engineers Inc., pp. 3135-3139, 2016 IEEE Region 10 Conference, TENCON 2016, Singapore, Singapore, 22-11-16. https://doi.org/10.1109/TENCON.2016.7848627

Thermal vision human classification and localization using bag of visual word. / Malpani, Sourabh; Asha, C. S.; Narasimhadhan, A. V.
Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 3135-3139 7848627 (IEEE Region 10 Annual International Conference, Proceedings/TENCON).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Thermal vision human classification and localization using bag of visual word

AU - Malpani, Sourabh

AU - Asha, C. S.

AU - Narasimhadhan, A. V.

PY - 2017/2/8

Y1 - 2017/2/8

N2 - Human detection in thermal images has recently gained a lot of attention in computer vision due to its large number of applications. The characteristics of thermal images are poor illumination, low contrast due to capturing devices and poor environment conditions. Human classification and localization are being done using bag of visual word method. Bag of visual word method has been widely used for visible spectrum. In this work, we have extended it to thermal images. A new human detection scheme is present for thermal image using SURF features with Bag of Word. SURF has been compared with different binary feature descriptors. SURF feature descriptor outperforms BRISK and FREAK feature descriptors in terms of accuracy, F-score.

AB - Human detection in thermal images has recently gained a lot of attention in computer vision due to its large number of applications. The characteristics of thermal images are poor illumination, low contrast due to capturing devices and poor environment conditions. Human classification and localization are being done using bag of visual word method. Bag of visual word method has been widely used for visible spectrum. In this work, we have extended it to thermal images. A new human detection scheme is present for thermal image using SURF features with Bag of Word. SURF has been compared with different binary feature descriptors. SURF feature descriptor outperforms BRISK and FREAK feature descriptors in terms of accuracy, F-score.

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DO - 10.1109/TENCON.2016.7848627

M3 - Conference contribution

AN - SCOPUS:85015446245

T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON

SP - 3135

EP - 3139

BT - Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2016 IEEE Region 10 Conference, TENCON 2016

Y2 - 22 November 2016 through 25 November 2016

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Malpani S, Asha CS, Narasimhadhan AV. Thermal vision human classification and localization using bag of visual word. In Proceedings of the 2016 IEEE Region 10 Conference, TENCON 2016. Institute of Electrical and Electronics Engineers Inc. 2017. p. 3135-3139. 7848627. (IEEE Region 10 Annual International Conference, Proceedings/TENCON). doi: 10.1109/TENCON.2016.7848627

Thermal vision human classification and localization using bag of visual word

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