@INPROCEEDINGS{1282Pätzold2010,
	AUTHOR = {Michael Pätzold and Rubén Heras Evangelio and Thomas Sikora},
	TITLE = {Counting People in Crowded Environments: An Overview},
	BOOKTITLE = {Hands-on Image Processing 2010 (HOIP10). Security, Surveillance and Identification in Everyday Life},
	YEAR = {2010},
	MONTH = nov,
	ORGANIZATION = {TECNALIA},
	ADDRESS = {TECNALIA. Technology Park building 202; 48170 Zamudio (Bizkaia)},
	NOTE = {invited paper},
	URL = {http://es.slideshare.net/TECNALIA/hoip10-articulo-1702univberlin},
	ABSTRACT = {Counting the number of persons in a crowded scene is of big interest in many applications. Most of the proposed approaches in the literature tackle the task of counting people in an indirect, statistical way. Recently, we presented a direct, counting-by-detection method based on fusing shape information obtained from an adapted Histogram of Oriented Gradients algorithm (HOG) with temporal information. The use of temporal information reduces false positives by considering the characteristics of motion of different human body parts. A subsequent tracking and coherent motion detection of the human hypotheses enhance the performance of this system additionally. The performance obtained by this system is comparable to state-of-the-art systems while allowing not only counting people but also providing valuable information for a tracking approach. In this paper we present an overview of relevant state-of-the-art methods for counting people in crowded environments, paying special attention to the method proposed by our group and showing results based on standard video sequences.}
}