A fusion framework for vision-based indoor occupancy estimation
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[1] Sinan Kalkan,et al. Vision-based estimation of the number of occupants using video cameras , 2022, Adv. Eng. Informatics.
[2] Xiaoteng Ma,et al. Mpsn: Motion-Aware Pseudo Siamese Network for Indoor Video Head Detection , 2021, SSRN Electronic Journal.
[3] Qianchuan Zhao,et al. Indoor occupancy measurement by the fusion of motion detection and static estimation , 2021, Energy and Buildings.
[4] Taeyeon Kim,et al. Review of vision-based occupant information sensing systems for occupant-centric control , 2021 .
[5] Petr Dolezel,et al. New End-to-End Strategy Based on DeepLabv3+ Semantic Segmentation for Human Head Detection , 2021, Sensors.
[6] Taeyeon Kim,et al. Application of vision-based occupancy counting method using deep learning and performance analysis , 2021 .
[7] Faouzi Alaya Cheikh,et al. TCM: Temporal Consistency Model for Head Detection in Complex Videos , 2020, J. Sensors.
[8] Zheng O'Neill,et al. Nationwide HVAC energy-saving potential quantification for office buildings with occupant-centric controls in various climates , 2020 .
[9] M. Melkemi,et al. MaskedFace-Net – A dataset of correctly/incorrectly masked face images in the context of COVID-19 , 2020, Smart Health.
[10] Jingsi Zhang,et al. Review on occupant-centric thermal comfort sensing, predicting, and controlling , 2020 .
[11] Ivan Mutis,et al. Real-time space occupancy sensing and human motion analysis using deep learning for indoor air quality control , 2020 .
[12] Qian Huang,et al. Development of CNN-based visual recognition air conditioner for smart buildings , 2020, J. Inf. Technol. Constr..
[13] Jianhong Zou,et al. A review of building occupancy measurement systems , 2020 .
[14] Liu Guanghui,et al. Real-time dynamic estimation of occupancy load and an air-conditioning predictive control method based on image information fusion , 2020 .
[15] Zheng O'Neill,et al. A review of smart building sensing system for better indoor environment control , 2019, Energy and Buildings.
[16] P. Vadakkepat,et al. Real-time identification of pedestrian meeting and split events from surveillance videos using motion similarity and its applications , 2019, Journal of Real-Time Image Processing.
[17] Chunhua Chen,et al. iOccupancy: An Investigation of Online Occupancy-driven HVAC Control in Campus Classrooms , 2018, CitiFog@SenSys.
[18] Ya Wang,et al. Occupancy Detection and Localization by Monitoring Nonlinear Energy Flow of a Shuttered Passive Infrared Sensor , 2018, IEEE Sensors Journal.
[19] Abbas Javed,et al. An Intelligent Real-Time Occupancy Monitoring System Using Single Overhead Camera , 2018, IntelliSys.
[20] Arun Kumar Chandran,et al. Comparison of different occupancy counting methods for single system-single zone applications , 2018, Energy and Buildings.
[21] Lihua Xie,et al. Building occupancy estimation and detection: A review , 2018, Energy and Buildings.
[22] Ardeshir Mahdavi,et al. Special issue on the fundamentals of occupant behaviour research , 2017 .
[23] S. N. Akshay Uttama Nambi,et al. Predicting Room-Level Occupancy Using Smart-Meter Data , 2017, Int. J. Distributed Syst. Technol..
[24] Qianchuan Zhao,et al. Occupancy detection in the office by analyzing surveillance videos and its application to building energy conservation , 2017 .
[25] Talal Rahwan,et al. Automatic HVAC Control with Real-time Occupancy Recognition and Simulation-guided Model Predictive Control in Low-cost Embedded System , 2017, ArXiv.
[26] Weng Khuen Ho,et al. A tracking cooling fan using geofence and camera-based indoor localization , 2017 .
[27] José Manuel Cejudo López,et al. A comparison of heating terminal units: Fan-coil versus radiant floor, and the combination of both , 2017 .
[28] Dimitrios Tzovaras,et al. Conditional Random Fields - based approach for real-time building occupancy estimation with multi-sensory networks , 2016 .
[29] Kaiming He,et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[30] Rita Streblow,et al. CO2 based occupancy detection algorithm: Experimental analysis and validation for office and residential buildings , 2015 .
[31] Burcin Becerik-Gerber,et al. A systematic approach to occupancy modeling in ambient sensor-rich buildings , 2014, Simul..
[32] Youtian Du,et al. Measuring indoor occupancy in intelligent buildings using the fusion of vision sensors , 2013 .
[33] Dipanjan Chakraborty,et al. Occupancy detection in commercial buildings using opportunistic context sources , 2012, 2012 IEEE International Conference on Pervasive Computing and Communications Workshops.
[34] Hélène Laurent,et al. Towards a sensor for detecting human presence and characterizing activity , 2011 .
[35] Xiaokang Yang,et al. Camshift Guided Particle Filter for Visual Tracking , 2007, 2007 IEEE Workshop on Signal Processing Systems.
[36] Sultan Daud Khan,et al. Robust Head Detection in Complex Videos Using Two-Stage Deep Convolution Framework , 2020, IEEE Access.
[37] Ya Wang,et al. A Low-Power Electric-Mechanical Driving Approach for True Occupancy Detection Using a Shuttered Passive Infrared Sensor , 2019, IEEE Sensors Journal.
[38] Tianzhen Hong,et al. The human dimensions of energy use in buildings: A review , 2018 .