Abstract
We present a vision based HCI system which exploits background subtraction comparing local orientation histograms. As a new virtual input device for game control, we focus on extracting coarse pose of the foreground object and its application to video game. The captured image is divided into the cells where the local orientation histogram with Gaussian kernel is computed and compared with the corresponding one using Bhattacharyya distance measure. The orientation histogram-based method is partially robust against illumination change and small moving objects in background. We also propose a vision-based interfacing system to existing game engines and appropriate modules that includes recognition process using neural network. The real-time 3D video games are implemented as a test-bed with the proposed system to prove the presented vision based system is highly applicable to let users control virtual environment without any hard-wired input devices.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jang, D.H., Chai, Y.J., Jin, X.H., Kim, T.Y.: Realtime Coarse Pose Recognition using a Local Integral Histogram. In: International Conference on Convergence Information Technology, November 21-23, pp. 1982–1987 (2007)
Mason, M., Duric, Z.: Using histograms to detect and track objects in color video. In: Applied Imagery Pattern Recognition Workshop, AIPR 2001 30th, IEEE, October 10-12, pp. 154–159 (2001)
Porkili, F.: Integral histogram: A fast way to extract histograms in cartesian spaces. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition (CVPR) (2005)
Noriega, P., Bascle, B., Bernier, O.: Local kernel color histograms for background subtraction. VISAPP, 1st edn., pp. 213–219. INSTICC Press (2006)
Noriega, P., Bernier, O.: Real Time Illumination Invariant Background Sub-traction Using Local Kernel Histograms. In: British Machine Vision Association (BMVC ) (2006)
Bradski, G.: Real time face and object tracking as a component of a perceptual user interface. In: Proc. IEEE WACV, pp. 214–219 (1998)
Viola, P., Jones, M.: Robust real time object detection. In: IEEE ICCV Workshop on Statistical and Computational Theories of Vision (2001)
Stauer, Grimson, W.E.L.: Adaptive background mixture models for real-time tracking. In: Computer Vision and Pattern Recognition Fort Collins, Colorado, June 1999, pp. 246–225 (1999)
Wixson, L.: Detecting salient motion by accumulating directionary-consistent flow. IEEE Trans. Pattern Anal. Machine Intell. 22, 774–780 (2000)
Yahav, G., Iddan, G.J., Mandelbaum, D.: 3D imaging Camera for Gaming Application. In: Consumer Electronics 2007. ICCE 2007. Digest of Technical Papers (2007)
Marimon, D., Ebrahimi, T.: Orientation histogram-based matching for region tracking. In: IEEE Eight International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS 2007) (2007)
Viola, P., Jones, M.: Robust real time object detection. In: IEEE ICCV Workshop on Statistical and Computational Theories of Vision (2001)
Li, L., Huang, W.M., Gu, I.Y.H., Tian, Q.: Foreground object detection in changing background based on color co-occurrence statistics. In: Proc. IEEE Workshop Applications of Computer Vision, December 2002, pp. 269–274 (2002)
Freeman, W., Tanaka, K., Ohta, J., Kyuma, K.: Computer vision for computer games. In: Int’l Workshop on Automatic Face- and Gesture-Recognition (1996)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jang, D.H., Jin, X.H., Kim, T.Y. (2008). Vision Based Pose Recognition in Video Game. In: Pan, Z., Zhang, X., El Rhalibi, A., Woo, W., Li, Y. (eds) Technologies for E-Learning and Digital Entertainment. Edutainment 2008. Lecture Notes in Computer Science, vol 5093. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69736-7_42
Download citation
DOI: https://doi.org/10.1007/978-3-540-69736-7_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69734-3
Online ISBN: 978-3-540-69736-7
eBook Packages: Computer ScienceComputer Science (R0)