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Cheng, Xiaogang
Publications (2 of 2) Show all publications
Cheng, X., Yang, B., Hedman, A., Olofsson, T., Li, H. & Van Gool, L. (2019). NIDL: A pilot study of contactless measurement of skin temperature for intelligent building. Energy and Buildings, 198, 340-352
Open this publication in new window or tab >>NIDL: A pilot study of contactless measurement of skin temperature for intelligent building
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2019 (English)In: Energy and Buildings, ISSN 0378-7788, E-ISSN 1872-6178, Vol. 198, p. 340-352Article in journal (Refereed) Published
Abstract [en]

Human thermal comfort measurement plays a critical role in giving feedback signals for building energy efficiency. A contactless measuring method based on subtleness magnification and deep learning (NIDL) was designed to achieve a comfortable, energy efficient built environment. The method relies on skin feature data, e.g., subtle motion and texture variation, and a 315-layer deep neural network for constructing the relationship between skin features and skin temperature. A physiological experiment was conducted for collecting feature data (1.44 million) and algorithm validation. The contactless measurement algorithm based on a partly-personalized saturation temperature model (NIPST) was used for algorithm performance comparisons. The results show that the mean error and median error of the NIDL are 0.476 degrees C and 0.343 degrees C which is equivalent to accuracy improvements of 39.07% and 38.76%, respectively.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Contactless method, Thermal comfort measurement, Vision-based subtleness magnification, Deep learning, Intelligent building
National Category
Building Technologies
Identifiers
urn:nbn:se:kth:diva-255723 (URN)10.1016/j.enbuild.2019.06.007 (DOI)000477091800027 ()
Note

QC 20190814

Available from: 2019-08-14 Created: 2019-08-14 Last updated: 2019-08-14Bibliographically approved
Yang, B., Cheng, X., Dai, D., Olofsson, T., Li, H. & Meier, A. (2019). Real-time and contactless measurements of thermal discomfort based on human poses for energy efficient control of buildings. Building and Environment, 162, Article ID UNSP 106284.
Open this publication in new window or tab >>Real-time and contactless measurements of thermal discomfort based on human poses for energy efficient control of buildings
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2019 (English)In: Building and Environment, ISSN 0360-1323, E-ISSN 1873-684X, Vol. 162, article id UNSP 106284Article in journal (Refereed) Published
Abstract [en]

Individual thermal discomfort perception gives important feedback signals for energy efficient control of building heating, ventilation and air conditioning systems. However, there is few effective method to measure thermal discomfort status of occupants in a real-time and contactless way. A novel method based on contactless measurements of human thermal discomfort status was presented. Images of occupant poses, which are related to thermoregulation mechanisms, were captured by a digital camera and the corresponding 2D coordinates were obtained. These poses were converted into skeletal configurations. An algorithm was developed to recognize different poses related to thermal discomfort, such as hugging oneself or wiping sweat off the brow. The algorithm could recognize twelve thermal discomfort related human poses. These poses were derived from a questionnaire survey of 369 human subjects. Some other human subjects participated in the validation experiments of the proposed method. All twelve thermal discomfort related poses can be recognized effectively.

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD, 2019
Keywords
Contactless measurement, Thermal discomfort, Human pose, Machine learning
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-261035 (URN)10.1016/j.buildenv.2019.106284 (DOI)000484514400018 ()2-s2.0-85070109030 (Scopus ID)
Note

QC 20191002

Available from: 2019-10-02 Created: 2019-10-02 Last updated: 2019-10-04Bibliographically approved
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