Total views : 195
Field Seeding Algorithm for People Counting Using KINECT Depth Image
In this work, we present a people counting algorithm using depth images acquired from a KINECT camera that is installed vertically, i.e., pointing toward the floor. Our proposed algorithm is referred to as Field seeding algorithm. The key idea is that first a set of local minimum values are detected from several spatially distributed seed locations. Then, the peoplehead blobs are detected from the binary images generated with regard to the threshold values derived from the local minimum values. The recall, accuracy and F-score of our algorithm are comparable to the current state-of-the-art people counting using KINECT, i.e. Water Filling. However, the main advantage over the previous method is that our algorithm operates deterministically, i.e., no any random number generating function is used.
Depth Image, Head Detection, People Counting, Vertical Kinect.
- Cho S, Chow T, Leung C. A neural-based crowd estimation by hybrid global learning algorithm. Institute of Electrical and Electronics Engineers (IEEE) Transactions on Systems, Man, and Cybernetics. 1999; 29(4):535–41.
- Dong L, Parameswaran V, Ramesh V, Zoghlami I. Fast crowd segmentation using shape indexing. Institute of Electrical and Electronics Engineers (IEEE) 11th International Conference on Computer Vision; 2007 Oct. p. 1–8.
- Kong D, Gray D, Tao H. Counting pedestrians in crowds using viewpoint invariant training. In Proceedings of the British Machine Vision Conference (BMVC), Oxford, UK; 2005 Sep.
- Marana A, Costa L, Lotufo R, Velastin S. On the efficacy of texture analysis for crowd monitoring. International Symposium on Computer Graphics, Image Processing, and Vision (SICGRAPI); 1998 Oct. p. 354–61.
- Velipasalar S, Tian YL, Hampapur A. Automatic counting of interacting people by using a single uncalibrated camera.Institute of Electrical and Electronics Engineers (IEEE) International Conference on Multimedia and Expo; 2006 Jul. p. 1265–8.
- Kong D, Gray D, Tao H. A viewpoint invariant approach for crowd counting. The 18th International conference on Pattern Recognition. 2006 Aug 20–24; 4:630–3.
- Chen TH, Chen TY, Chen ZX. An intelligent people-flow counting method for passing through a gate. Institute of Electrical and Electronics Engineers (IEEE) Conference on Robotics, Automation and Mechatronics; 2006 Jun 1–3. p.1–6.
- Terada K, Yoshida D, Oe S, Yamaguchi J. A counting method of the number of passing people using a stereo camera. The 25th Annual Conference of the Institute of Electrical and Electronics Engineers (IEEE). 1999 Nov 29 – Dec 3; 3:1318–23.
- Beymer D. Person counting using stereo. In the Proceedings of Institute of Electrical and Electronics Engineers (IEEE) Workshop on Human Motion; 2000. p. 127–33.
- Zhang X, Yan J, Feng S, Lei Z, Yi D, Li S. Water filling: unsupervised people counting via Kinect sensor. Institute of Electrical and Electronics Engineers (IEEE) Ninth International Conference on Advanced Video and SignalBased Surveillance (AVSS); 2012. p. 215–20.
- Hsieh CT, Wang HC, Wu YK, Chang LC, Kuo TK. A Kinect based people flow counting system. International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS); 2012 Nov 4–7. p.146–50.
- Alexandru T. An image in painting technique based on the fast marching method. Journal of graphics tools. 2004; 9(1):23–34.
- Kaewtrakulpong P, Bowden R. A real time adaptive visual surveillance system for tracking low-resolution colour targets in dynamically changing scenes. Image and Vision Computing. 2003 Sep; 21(10):913–29.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.