Alessandro Moro
ABSTRACT
In this paper, a method for automatically building 3D virtual worlds which correspond to the the objects detected in a real environment is presented. The proposed method can be used in many applications such as for example Virtual Reality, Augmented Reality, remote inspection and Virtual Worlds generation. Our method requires an operator equipped with a stereo camera and moving in an office environment. The operator takes a picture of the environment and, with the proposed method, the Regions of Interest (ROI) are extracted from each picture, their content is classified and 3D virtual scenarios are reconstructed using icons which resemble the classified object categories. ROI extraction, pose and height estimation of the classified objects are performed using stereo vision. The ROIs are obtained using a Dempster-Shafer technique for fusing different information detected from the image such as the Speeded Up Robust Features (SURF) and depth data obtained with the stereo camera. Experimental results are presented in office environments.
- D. Anguelov, D. Koller, E. Parker, and S. Thrun. Detecting and modeling doors with mobile robots. In IEEE International Conference on Robotics and Automation - ICRA, pages 3777--3784, 2004.Google Scholar
Cross Ref
- H. Bay, A. Ess, T. Tuytelaars, and L. Van Gool. Speeded-up robust features (surf). Comput. Vis. Image Underst., 110(3):346--359, 2008. Google ScholarDigital Library
- S. Brezetz, R. Chatilaand, and M. Devy. Natural scene understanding for mobile robot navigation. In IEEE International Conference on Robotics and Automation - ICRA, pages 730--736, 1994.Google ScholarCross Ref
- J. Canny. A computational approach to edge detection. IEEE Trans. on Pattern Analysis and Machine Intelligence, 8(6):679--698, 1986. Google ScholarDigital Library
- P. grey. Bumbleebee. http://www.ptgrey.com.Google Scholar
- M. Khoury, X. Shen, and S. Shirmohammadi. A peer-to-peer collaborative virtual environment for e-commerce. In Canadian Conference on Electrical and Computer Engineering, pages 828--831, 2007.Google ScholarCross Ref
- B. Limketkai, L. Liao, and D. Fox. Relational object maps for mobile robots. In International Joint Conference on Artificial Intelligence - IJCAI, pages 1471--1476, 2005. Google ScholarDigital Library
- D. G. Lowe. Object recognition from local scale-invariant features. In International Conference on Computer Vision, pages 1150--1157, 1999. Google ScholarDigital Library
- D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60(2):91--110, 2004. Google ScholarDigital Library
- J. Modayil and B. Kuipers. Autonomous shape model learning for object localization and recognition. In International Conference on Robotics and Automation - ICRA, pages 2991--2996, 2006.Google ScholarCross Ref
- M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit. Fastslam: A factored solution to the simultaneous localization and mapping problem. In Proceedings of the 18th National Conference on Artificial Intelligence - AAAI, pages 593--598, July 2002. Google ScholarDigital Library
- A. Moro, E. Mumolo, and M. Nolich. Visual scene analysis using relaxation labeling and embedded hidden markov models for map-based robot navigation. In International Conference on Information Technology Interfaces - ITI, pages 767--772, 2008.Google ScholarCross Ref
- O. Mozos, R. Triebel, P. Jensfelt, A. Rottmann, and W. Burgard. Supervised semantic labeling of places using information extracted from sensor data. Robotics and Autonomous Systems, 55(5):391--402, 2007. Google ScholarDigital Library
- A. V. Nefian and M. H. Hayes-III. An embedded hmm based approach for face detection and recognition. In IEEE International Conference on Acoustic Speech and Signal Processing, pages 3553--3556, 1999. Google ScholarDigital Library
- L. Overbey, G. McKoy, J. Gordon, and S. McKitrick. Automated sensing and social network analysis in virtual worlds. In International Conference on Intelligence and Security Informatics, pages 179--184, 2008.Google Scholar
- M. Pietikäineng. Image Analysis. Lecture Notes in Computer Science. Springer, 2005.Google Scholar
- A. Ranganathan and F. Dellaert. Semantic modeling of places using objects. In Proceedings of Robotics: Science and Systems, Atlanta, GA, USA, 2007.Google ScholarCross Ref
- G. Shafer. A Mathematical Theory of Evidence. Princeton University Press, 1976.Google Scholar
- C. Sun, Z. Pan, and Y. Li. Srp based natural interaction between real and virtual worlds in augmented reality. In International Conference on Cyberworlds, pages 117--124, 2008. Google ScholarDigital Library
- M. Tomono. 3-d object map building using dense object models with sift-based recognition features. In IEEE Int. Conf. of Intelligent Robots and Systems - IROS, pages 1885--1890, 2006.Google ScholarCross Ref
- S. Vasudevan, S. Gachter, M. Berger, and R. Siegwart. Cognitive maps for mobile robots - an object based approach. Robotics and Autonomous Systems, 55(5):359--371, 2007. Google ScholarDigital Library
- S. Vosinakis and T. Panayiotopoulos. A tool for constructing 3d environments with virtual agents. Multimedia Tools and Applications archive, 25(2):253--279, 2005. Google ScholarDigital Library
- M. Xiang, D. Schonfeld, and A. Khokhar. A general two-dimensional hidden markov model and its application in image classification. In IEEE International Conference on Image Processing ICIP, pages VI41-VI44, 2007.Google Scholar
Index Terms
- Building virtual worlds by 3d object mapping
Recommendations
Catadioptric Stereo Using Planar Mirrors
By using mirror reflections of a scene, stereo images can be captured with a single camera (catadioptric stereo). In addition to simplifying data acquisition single camera stereo provides both geometric and radiometric advantages over traditional two ...
Controlling virtual cameras based on a robust model-free pose acquisition technique
This paper presents a novel method that acquires camera position and orientation from a stereo image sequence without prior knowledge of the scene. To make the algorithm robust, the Interacting Multiple Model Probabilistic Data Association Filter (...
Build Virtual Reality of 3D Landscape Based on Precise Time and Space and Application Methods Research
ICMTMA '14: Proceedings of the 2014 Sixth International Conference on Measuring Technology and Mechatronics AutomationThis paper presents a virtual reality system concept what can adapt human eye binocular stereo vision and measure the three-dimensional accurately and describes the social needs, theoretical and building technology of this system. The paper specifically ...
Comments