Vision-based indoor occupants detection system for intelligent buildings

Dixin Liu; Youtian Du; Qianchuan Zhao; Xiaohong Guan

doi:10.1109/IST.2012.6295489

Vision-based indoor occupants detection system for intelligent buildings

Dixin Liu
, Youtian Du
, Qianchuan Zhao
, Xiaohong Guan

Faculty of Electronic and Information Engineering

Tsinghua University
Xi'an Jiaotong University

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

8 Scopus citations

Abstract

In intelligent buildings, practical sensing systems designed to gather indoor occupancy information play an indispensable role in improving occupant comfort and energy efficiency by optimizing control strategies of HVAC (Heating, Ventilation and Air Conditioning) system and lighting system. In this paper we propose a novel method for occupant detection based on video surveillances now widely used in buildings. In our method, a two-staged static detector using both Haar-like and HOG (Histograms of Oriented Gradients) features and a template-based motion analysis module are concatenated to detect the heads of occupants rapidly and effectively. The accuracy can satisfy the requirements of the automation systems in intelligent buildings. Experimental results demonstrate the effectiveness and efficiency of the proposed method.

Original language	English
Title of host publication	IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings
Pages	273-278
Number of pages	6
DOIs	https://doi.org/10.1109/IST.2012.6295489
State	Published - 2012
Event	2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012 - Manchester, United Kingdom Duration: 16 Jul 2012 → 17 Jul 2012

Publication series

Name	IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings

Conference

Conference	2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012
Country/Territory	United Kingdom
City	Manchester
Period	16/07/12 → 17/07/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Occupant detection
intelligent building
video surveillance

Access to Document

10.1109/IST.2012.6295489

Cite this

Liu, D., Du, Y., Zhao, Q., & Guan, X. (2012). Vision-based indoor occupants detection system for intelligent buildings. In IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings (pp. 273-278). Article 6295489 (IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings). https://doi.org/10.1109/IST.2012.6295489

@inproceedings{38f479b417a94c60a2371104aec436cb,

title = "Vision-based indoor occupants detection system for intelligent buildings",

abstract = "In intelligent buildings, practical sensing systems designed to gather indoor occupancy information play an indispensable role in improving occupant comfort and energy efficiency by optimizing control strategies of HVAC (Heating, Ventilation and Air Conditioning) system and lighting system. In this paper we propose a novel method for occupant detection based on video surveillances now widely used in buildings. In our method, a two-staged static detector using both Haar-like and HOG (Histograms of Oriented Gradients) features and a template-based motion analysis module are concatenated to detect the heads of occupants rapidly and effectively. The accuracy can satisfy the requirements of the automation systems in intelligent buildings. Experimental results demonstrate the effectiveness and efficiency of the proposed method.",

keywords = "Occupant detection, intelligent building, video surveillance",

author = "Dixin Liu and Youtian Du and Qianchuan Zhao and Xiaohong Guan",

year = "2012",

doi = "10.1109/IST.2012.6295489",

language = "英语",

isbn = "9781457717741",

series = "IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings",

pages = "273--278",

booktitle = "IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings",

note = "2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012 ; Conference date: 16-07-2012 Through 17-07-2012",

}

Liu, D, Du, Y, Zhao, Q & Guan, X 2012, Vision-based indoor occupants detection system for intelligent buildings. in IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings., 6295489, IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings, pp. 273-278, 2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012, Manchester, United Kingdom, 16/07/12. https://doi.org/10.1109/IST.2012.6295489

Vision-based indoor occupants detection system for intelligent buildings. / Liu, Dixin; Du, Youtian; Zhao, Qianchuan et al.
IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings. 2012. p. 273-278 6295489 (IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings).

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

TY - GEN

T1 - Vision-based indoor occupants detection system for intelligent buildings

AU - Liu, Dixin

AU - Du, Youtian

AU - Zhao, Qianchuan

AU - Guan, Xiaohong

PY - 2012

Y1 - 2012

N2 - In intelligent buildings, practical sensing systems designed to gather indoor occupancy information play an indispensable role in improving occupant comfort and energy efficiency by optimizing control strategies of HVAC (Heating, Ventilation and Air Conditioning) system and lighting system. In this paper we propose a novel method for occupant detection based on video surveillances now widely used in buildings. In our method, a two-staged static detector using both Haar-like and HOG (Histograms of Oriented Gradients) features and a template-based motion analysis module are concatenated to detect the heads of occupants rapidly and effectively. The accuracy can satisfy the requirements of the automation systems in intelligent buildings. Experimental results demonstrate the effectiveness and efficiency of the proposed method.

AB - In intelligent buildings, practical sensing systems designed to gather indoor occupancy information play an indispensable role in improving occupant comfort and energy efficiency by optimizing control strategies of HVAC (Heating, Ventilation and Air Conditioning) system and lighting system. In this paper we propose a novel method for occupant detection based on video surveillances now widely used in buildings. In our method, a two-staged static detector using both Haar-like and HOG (Histograms of Oriented Gradients) features and a template-based motion analysis module are concatenated to detect the heads of occupants rapidly and effectively. The accuracy can satisfy the requirements of the automation systems in intelligent buildings. Experimental results demonstrate the effectiveness and efficiency of the proposed method.

KW - Occupant detection

KW - intelligent building

KW - video surveillance

UR - https://www.scopus.com/pages/publications/84870668014

U2 - 10.1109/IST.2012.6295489

DO - 10.1109/IST.2012.6295489

M3 - 会议稿件

AN - SCOPUS:84870668014

SN - 9781457717741

T3 - IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings

SP - 273

EP - 278

BT - IST 2012 - 2012 IEEE International Conference on Imaging Systems and Techniques, Proceedings

T2 - 2012 IEEE International Conference on Imaging Systems and Techniques, IST 2012

Y2 - 16 July 2012 through 17 July 2012

ER -

Vision-based indoor occupants detection system for intelligent buildings

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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