이승용 교수

In multi-class indoor semantic segmentation using RGB-D data, it has been shown that incorporating depth feature into RGB feature is helpful to improve segmentation accuracy. However, previous studies have not fully exploited the potentials of multi-modal feature fusion, e.g., simply concatenating RGB and depth features or averaging RGB and depth score maps. To learn the optimal fusion of multimodal features, this paper presents a novel network that extends the core idea of residual learning to

This paper describes an image metamorphosis technique to handle scattered feature constraints specified with points, polylines, and splines. Solutions to the following three problems are presented: feature specification, warp generation, and transition control. We demonstrate the use of snakes to reduce the burden of feature specification. Next, we propose the use of multilevel free-form deformations (MFFD) to compute C/sup 2/-continuous and one-to-one mapping functions among the specified featu

This paper presents a new image morphing method using a two-dimensional deformation technique which provides an intuitive model for a warp. The deformation technique derives aC1-continuous and one-to-one warp from a set of point pairs overlaid on two images. The resulting in-between image precisely reflects the correspondence of features specified by an animator. We also control the transition behaviour in a metamorphosis sequence by taking another deformable surface model, which is simpler and

Polymorph extends conventional morphing to derive morphed images from more than two images at once, effectively integrating geometric manipulations and color blending. We present a general framework for polymorphing by extending the traditional image morphing paradigm that applies to two images. The authors formulate each input image as a vertex of an (n-1)-dimensional simplex, where n equals the number of input images. They look at the mathematical framework for polymorph, followed by warp func

Abstract This paper presents a novel filtering‐based method for decomposing an image into structures and textures. Unlike previous filtering algorithms, our method adaptively smooths image gradients to filter out textures from images. A new gradient operator, the interval gradient, is proposed for adaptive gradient smoothing. Using interval gradients, textures can be distinguished from structure edges and smoothly varying shadings. We also propose an effective gradient‐guided algorithm to produc

Abstract This paper presents a simple algorithm for producing stylistic abstraction of a photograph. Based on mean curvature flow in conjunction with shock filter, our method simplifies both shapes and colors simultaneously while preserving important features. In particular, we develop a constrained mean curvature flow, which outperforms the original mean curvature flow in conveying the directionality of features and shape boundaries. The proposed algorithm is iterative and incremental, and ther

This paper presents a novel approach to multiresolution editing of a triangular mesh. The basic idea is to embed an editing area of a mesh onto a 2D rectangle and interpolate the user‐specified editing information over the 2D rectangle. The result of the interpolation is mapped back to the editing area and then used to update the mesh. We adopt harmonic maps for the embedding and multilevel B‐splines for the interpolation. The proposed mesh editing technique can handle an arbitrary mesh without