Browsing by Author "Fayek M."

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    HSBS: A human's heat signature and background subtraction hybrid approach for crowd counting and analysis
    (World Scientific Publishing Co. Pte Ltd, 2016) Negied N.K.A.-W.; Hemayed E.B.; Fayek M.; Faculty of Computer Science; MSA University; Giza; 6th of October City; Cairo; Egypt; Computer Engineering Department; Faculty of Engineering; Cairo University; Cairo University Road; Oula; Giza; Egypt
    This work presents a new approach for crowd counting and classification based upon human thermal and motion features. The technique is efficient for automatic crowd density estimation and type of motion determination. Crowd density is measured without any need for camera calibration or assumption of prior knowledge about the input videos. It does not need any human intervention so it can be used successfully in a fully automated crowd control systems. Two new features are introduced for crowd counting purpose: the first represents thermal characteristics of humans and is expressed by the ratio between their temperature and their ambient environment temperature. The second describes humans motion characteristics and is measured by the ratio between humans motion velocity and the ambient environment rigidity. Each ratio should exceed a certain predetermined threshold for human beings. These features have been investigated and proved to give accurate crowd counting performance in real time. Moreover, the two features are combined and used together for crowd classification into one of the three main types, which are: fully mobile, fully static, or mix of both types. Last but not least, the proposed system offers several advantages such as being a privacy preserving crowd counting system, reliable for homogeneous and inhomogeneous crowds, does not depend on a certain direction in motion detection, has no restriction on crowd size. The experimental results demonstrate the effectiveness of the approach. � 2016 World Scientific Publishing Company.