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Ing. Radek Richtr, Ph.D.

Publikace

Dynamic Texture Similarity Criterion

Rok
2018
Publikováno
2018 24rd International Conference on Pattern Recognition (ICPR). Piscataway, NJ: IEEE, 2018. p. 904-909. ISSN 1051-4651. ISBN 978-1-5386-3788-3.
Typ
Stať ve sborníku
Anotace
Evaluating the likeness of two similar dynamic textures or dynamic textures of the same type is still a challenging and unresolved problem. Temporal dimension and dynamics in texture complicates the problem of mere texture similarities and makes it even more challenging. A simple approach to compute difference between DTs bag of features, STSIM of pure statistisc methods are insufficient and does not affect the variable texture dynamics which is crucial for human recognition. Testing the similarity, quality and fidelity of both natural and arftificial dynamic textures is a problem that can be solved by psychometric tests with users, but these are challenging both in terms of time, human resources and data processing. The solution provided by us compares the frequency and regularity of the time behavior of spatial frequencies in texture with great consistency with the values provided by users testing. The solution itself provides a functional metric that can be used to evaluate the similarity of textures modified by inpainting, retouching as well as evaluating the similarity of the dynamics across the type of the DTs.

Dynamic Texture Editing

Rok
2015
Publikováno
Proceedings of the 31st Spring Conference on Computer Graphics. New York: ACM, 2015. p. 133-140. ISBN 978-1-4503-3693-2.
Typ
Stať ve sborníku
Anotace
A fast simple method for dynamic textures enlargement and editing is presented. The resulting edited dynamic texture is a mixture of several color dynamic textures that realistically matches the given color textures appearance and respects their original optical flows. The method simultaneously allows to spatially and temporarily enlarge the original dynamic textures to fill any required four dimensional dynamic texture space. The method is based on a generalization of the prominent static double toroid-shaped texture modeling roller method to the dynamic texture domain. The presented method keeps the original static texture roller principle of separated analysis and synthesis parts of the algorithm. In its analytical step, the input textures patches are found by an optimal overlap tiling and the subsequent minimum boundary cut. The optimal toroid-shaped dynamic texture patches are created in each spatial and time dimension, respectively. The spatial dimension tile border is derived by textural features, color-tone, and the minimal overlapping error. The time dimension tile border is detected by minimizing the overlapping error and using the input textures optical flow. The realistic appearance of the dynamic textures mix requires to edit the patch color space and to find border patches which consists from more than one type of the texture. These border patches are found similarly to the multi-texture analysis patch step. Since all time-consuming processing, such as the finding of optimal spatio-temporal triple toroidal patches, are done in the analytical step which is completely separated from synthesis part, the synthesis of the edited and enlarged resulting texture can by done very efficiently by applying simple set of repeating rules for these triple toroidal patches. Thus the presented method is extremely fast and capable to synthesize a learned natural dynamic texture spatially and its time span in real-time.

Dynamic Texture Enlargement

Rok
2013
Publikováno
29th Proceedings Spring Conference on Computer Graphics 2013. Bratislava: Comenius University, 2013, pp. 13-20. ISBN 978-80-223-3377-1. Available from: http://www.sccg.sk
Typ
Stať ve sborníku
Anotace
A simple fast approach for dynamic texture synthesize that realistically matches given color or multispectral texture appearance and respects its original optic flow is presented. The method generalizes the prominent static double toroid-shaped texture modeling method to the dynamic texture synthesis domain. The analytical part of the method is based on optimal overlapping tiling and subsequent minimum boundary cut. The optimal toroid-shaped dynamic texture patches are created in each spatial and time dimension, respectively. The time dimension tile border is derived from the optical flow of the modeled texture. The toroid-shaped tiles are created in the analytical step which is completely separated from the synthesis part. Thus the presented method is extremely fast and capable to enlarge a learned natural dynamic texture spatially and temporally in real-time.