Abstract
Different hardware implementations of designed automatic 2D to 3D video color conversion employing 2D video and sequence are presented. The analyzed frameworks include together processing of neighboring frames using the following blocks: CIELa*b* color space conversion, wavelet transform (WT) with edge detection using HF wavelet sub-bands (HF, LH and HH) or pyramidal scheme, color segmentation via k-means on a*b* color plane, up-sampling in wavelet case, disparity map (DM) estimation, adaptive post-filtering, and finally, the anaglyph 3D scene generation. The SSIM and QBP criteria are applied in order to compare the performance of the proposed frameworks against other 3D computation techniques. The designed techniques has been implemented on DSP TMS320DM648, Matlab’s Simulink module over a PC with Windows 7, and using graphic card (NVIDIA Quadro K2000) demonstrating that the proposed approach can be applied in real-time processing mode.
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Gonzalez-Huitron, V., Ramos-Diaz, E., Kravchenko, V., Ponomaryov, V. (2014). 2D to 3D Conversion Based on Disparity Map Estimation. In: Bayro-Corrochano, E., Hancock, E. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2014. Lecture Notes in Computer Science, vol 8827. Springer, Cham. https://doi.org/10.1007/978-3-319-12568-8_119
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DOI: https://doi.org/10.1007/978-3-319-12568-8_119
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