6533b7d6fe1ef96bd1267272
RESEARCH PRODUCT
Color and Flow Based Superpixels for 3D Geometry Respecting Meshing
Mohamad Motasem NawafAlain TrémeauMd. Abul HasnatDésiré Sidibésubject
Color histogramComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONOptical flow010103 numerical & computational mathematics02 engineering and technologyImage segmentation01 natural sciencesWeightingDistribution (mathematics)[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]Flow (mathematics)Computer Science::Computer Vision and Pattern Recognition[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligence0101 mathematicsbusinessRepresentation (mathematics)Adaptive opticsComputingMilieux_MISCELLANEOUSdescription
We present an adaptive weight based superpixel segmentation method for the goal of creating mesh representation that respects the 3D scene structure. We propose a new fusion framework which employs both dense optical flow and color images to compute the probability of boundaries. The main contribution of this work is that we introduce a new color and optical flow pixel-wise weighting model that takes into account the non-linear error distribution of the depth estimation from optical flow. Experiments show that our method is better than the other state-of-art methods in terms of smaller error in the final produced mesh.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2014-03-24 |