Boguslaw Cyganek
ABSTRACT
In this paper we present architecture and functionality of the visual multi-tool designed for acquisition of ground-truth and reference data for computer vision experimentation. The multi-tool allows three main functions, namely manual matching of the corresponding points for multi-view correlation, outlining of the image objects with polygons, as well as selection of characteristic points in specific image areas. These functions allows gathering of experimental data which are used for training and/or verification in such computer vision methods as stereo correlation, road signs detection and recognition, as well as color based segmentation. We present overview of the experimental results which were made possible with this multi-tool, as well as we discuss its potential further applications and extensions. The presented software platform was made available on the Internet.
- Cyganek, B. 2007. Circular Road Signs Recognition with Soft Classifiers. Integrated Computer-Aided Engineering, IOS Press, Vol. 14, No 4/, 2007, 323--343. Google Scholar
Digital Library
- Cyganek, B. 2008. Color Image Segmentation with Support Vector Machines: Applications To Road Signs Detection. Int. Journal of Neural Systems, Vol. 18, No. 4, World Scientific Publishing Company, 2008, 339--345.Google ScholarCross Ref
- Cyganek, B., Siebert J. P. 2009. An Introduction to 3D Computer Vision Techniques and Algorithms, Wiley. Google ScholarDigital Library
- Cyganek, B. 2012. One-Class Support Vector Ensembles for Image Segmentation and Classification. Journal of Mathematical Imaging & Vision, Vol. 42, No. 2--3, Springer 103--117. Google ScholarDigital Library
- Fisher, R., Dawson-Howe, K., Fitzgibbon, A., Robertson, C., Trucco E. 2005. Dictionary of Computer Vision and Image Processing, Wiley. Google ScholarDigital Library
- http://www.fltk.org/Google Scholar
- http://home.agh.edu.pl/~cyganek/CVMultiTool.zipGoogle Scholar
- http://msdn.microsoft.com/en-us/Google Scholar
- Johnson, J. 2011. Designing with the Mind in Mind: Simple Guide to Understanding User Interface Design Rules. Google ScholarDigital Library
- Tidwell, J. 2011. Designing Interfaces. O'Reilly Media. Google ScholarDigital Library
- Scharstein, D., Szeliski, R. 2002. A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. Int. J. of Computer Vision, Vol. 47, No. 1, 7--42. Google ScholarDigital Library
Index Terms
- A multi-tool for ground-truth stereo correspondence, object outlining and points-of-interest selection
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