Title :
A robust method for counting people in complex indoor spaces
Author_Institution :
Coll. of Inf. Eng., North China Univ. of Technol., Beijing, China
Abstract :
People counting systems have wide potential applications including video surveillance and public resources management. This paper describes a robust method for counting people in complex indoor spaces. The method has counted the number of people using a single camera in the indoor spaces through four modules: image pre-processing module, morphology processing module, image marking module and people counting module, in order to master the information of the indoor for increasing efficiency and utilization of building facilities. Through experiment comparing, image pre-processing module chooses image graying, background subtraction based on threshold, median filtering and threshold segmentation to eliminate background interference. The morphology processing module uses the improved erosion operation and the improved dilation operation to extract target feature. Then the following image marking module uses connected component detection algorithm, setting the object feature and shape judgment condition and marking object region. Finally, people counting module is used to count the number of people. Experimental results show that the robust method can perform accurate people counting. The method is easily realized and suitable for the complex small-scale indoor spaces.
Keywords :
cameras; feature extraction; image segmentation; image sequences; interference suppression; median filters; object detection; background interference elimination; background subtraction threshold; complex indoor spaces; connected component detection algorithm; image graying; image marking module; image preprocessing module; image sequences; median filtering; morphology processing module; object detection method; object region marking; people counting system method; public resource management; shape judgment condition; single camera; target feature extraction; threshold segmentation; video surveillance; Cameras; Data mining; Feature extraction; Filtering; Image segmentation; Interference elimination; Morphology; Resource management; Robustness; Video surveillance; background subtraction; image marking; morphology processing; people counting; threshold segmentation;
Conference_Titel :
Education Technology and Computer (ICETC), 2010 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-6367-1
DOI :
10.1109/ICETC.2010.5529346