Image Depth Detection System
DOI:
https://doi.org/10.18372/1990-5548.73.17008Keywords:
stereo vision, disparity map, depth map, calibration, rectification, image filteringAbstract
The article will be intended to explain the Image Depth Detection System, which in turn should perform all the necessary functions for detecting objects on a 3D scene, obtaining information about the sizes of bodies, and determining distances to certain bodies. Since such systems already exist in the modern world, the main goal was to create a model that meets the requirements regarding price-quality, since systems of this type currently on the market have a high cost price. Also, the improvement of the method of determining the depth of the image in this system was created thanks to the analysis of filtering methods available in the Matlab environment. An analysis of operation in different conditions of use, i.e. in the presence of external disturbances, such as daylight on the street, has been created.
References
Where is computer vision used today. World Trade Center.URL:https://corp.wtcmoscow.ru/services/international-partnership/actual/gde-segodnya-primenyaetsya-kompyuternoe-zrenie/ [in Russian].
L. A. Kotyuzhansky Calculation of the depth map of the stereo image on the GPU in real time. Basic research. no. 6–2, 2012, pp. 444–449. [in Russian].
D. Scharstein and R. Szeliski, "A taxonomy and evaluation of dense two-frame stereo correspondence algorithms," Int. Journal of Computer Vision 47. April-June 2002, pp. 7–42.
A. T. Vakhitov, L. S. Gurevich, and D. V. Pavlenko, "Review of stereo vision algorithms," Stochastic optimization in computer science, vol. 4, no. 1-1, 2008, pp. 151–169 [in Russian].
E. S. Ilyasov, "Calculation of the distance to the observed object from the images of the stereopair," Young scientist. International scientific journal, no. 14(118), 2016, pp. 146–151. [in Russian].
I. Cabezas, M. Trujillo, "A Non-linear Quantitative Evaluation Approach for Disparity Estimation," in: Proc. Intl. Joint Conf. on Computer Vision and Computer Graphics Theory and Applications, 2011, pp. 704–709.
H. Hirschmuller and D. Scharstein, "Evaluation of Stereo Matching Costs on Images with Radiometric Differences," IEEE Trans. Pattern Analysis and Machine Intelligence, 2009, 1582–1599. https://doi.org/10.1109/TPAMI.2008.221
Richard Hartley and Andrew Zisserman, Multiple View Geometry in Computer Vision. Second Edition pp. 178–193, pp. 458–493.
Maryna Mukhina, "Comparison of error metrics in matching algorithms of images by surf detector," Proсeedings of the National Aviation University, 2014, no. 4, pp. 128–132. https://doi.org/10.18372/2306-1472.61.7603
G. J. Iddan and G. Yahav, "3D imaging in the studio and elsewhere," Proc. SPIE, vol. 4298, 1994, pp. 48–55.
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
