Top-view people counting in public transportation using Kinect

• Autorzy: Malawski F.
• Języki publikacji: EN

Abstrakty

EN

This article describes a method for people counting in public transportation. In this particular scenario, various body poses corresponding to holding handrails must be accounted for. Kinect sensor mounted vertically has been employed to acquire a database of images of 1-5 persons, with and without body poses of holding a handrail. An algorithm has been devised for robust people counting, consisting of multiple steps. The handrails are removed by substituting an average image of the handrails from the image with persons holding a handrail. The image is then processed in blocks in order to find potential local maxima, which are subsequently verified to find head candidates. Finally, non-head objects are filtered out, based on the ratio of pixels with similar and near-zero value, in the neighbourhood of the maxima. The method has an average accuracy of 91% and has proved to handle well the handrails in the depth maps.

Słowa kluczowe

EN

people counting; Kinect; public transportation

PL

liczenie ludzi; Kinect; transport publiczny

• Wydawca: Foundation for Young Scientists
• Czasopismo: Challenges of Modern Technology
• Rocznik: 2014
• Tom: Vol. 5, no. 4
• Strony: 17--20
• Opis fizyczny: Bibliogr. 8 poz., rys., tab.

Twórcy

autor

Malawski F.

• AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunication, Department of Computer Science, al. Mickiewicza 30, 30-059 Krakow, Poland

Bibliografia

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• 2. Patzold M., Evangelio R. H., & Sikora T.: „Counting people in crowded environments by fusion of shape and motion information.„ In Advanced Video and Signal Based Surveillance (AVSS), 2010 Seventh IEEE International Conference on (pp. 157-164), Aug. 2010
• 3. Bevilacqua A., Di Stefano L., & Azzari P. „People Tracking Using a Time-of-Flight Depth Sensor.” In AVSS (Vol. 6, p. 89), Nov. 2006
• 4. Bondi E., Seidenari L., Bimbo A. D., Bagdanov A. D.: „Realtime people counting from depth imagery of crowded environments.” IEEE Computer Vision, 2003
• 5. Zhang X., Yan J., Feng S., Lei Z., Yi D., & Li S. Z.: „Water filling: Unsupervised people counting via vertical kinect sensor.„In Advanced Video and Signal-Based Surveillance (AVSS), 2012 IEEE Ninth International Conference on (pp. 215-220). Sept. 2012
• 6. Rauter M.: „Reliable human detection and tracking in top-view depth images.„ In Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on (pp. 529- 534), June 2013
• 7. Dan B. K., Kim Y. S., Jung J. Y., & Ko S. J.: „Robust people counting system based on sensor fusion.„ Consumer Electronics, IEEE Transactions on, 58(3), pp. 1013-1021, 2012
• 8. Wateosot C., & Suvonvorn N.: „Top-view Based People Counting Using Mixture of Depth and Color Information.„ The Second Asian Conference on Information Systems, ACIS 2013, October 31 – November 2 , 2013, Phuket, Thailand