Kyunghyun Yoon

Directional texture transfer

A texture transfer algorithm modifies the target image replacing the high frequency information with the example source image. Previous texture transfer techniques normally use such factors as color distance and standard deviation for selecting the best texture from the candidate sets. These factors are useful for expressing a texture effect of the example source in the target image, but are less than optimal for considering the object shape of the target image. In this paper, we propose a novel texture transfer algorithm to express the directional effect based on the flow of the target image. For this, we use a directional factor that considers the gradient direction of the target image. We add an additional energy term that respects the image gradient to the previous fast texture transfer algorithm. Additionally, we propose a method for estimating the directional factor weight value from the target image. We have tested our algorithm with various target images. Our algorithm can express a result image with the feature of the example source texture and the flow of the target image.

Extended papers from NPAR 2010: Directional texture transfer with edge enhancement

Texture transfer re-renders a target image with high-frequency information (texture) taken from parts of a reference image that is matched locally to the target image using characteristics such as color. In this paper, we add a directional factor based on the flow of the target image, creating a stroke-like effect that follows edges more accurately. In addition, we propose a method to clearly express object boundaries by considering the effect of the medium on edges in the reference image. We also show how to select an appropriate weight for this directional factor from the reference image. We demonstrate the suitability of this improved form of texture transfer for expressing various artistic styles, and compare our results with those from previous texture-transfer algorithms. We find that our algorithm can be adapted to texture synthesis as well.

A study on stackable mosaic generation for mobile devices

With the growing use of mobile devices such as smartphones, tablet PCs, and digital cameras, photography has become an integral part of everyday life. In particular, mobile devices with cameras allow us to easily capture and modify photographs that can be shared via social networks. In this paper, we introduce a mobile device application for converting photographs into photomosaic images. In general, high-quality photomosaics require large databases. However, mobile devices have limited resources; hence it is difficult for such devices to support photomosaics. We propose a method that produces a photomosaic effect using a database that consists of rotatable images. We also propose a solution to the performance issue based on a best match search.

Color juxtaposition for pointillism based on an artistic color model and a statistical analysis

We analyze characteristics and patterns of color juxtaposition and the color theory used by pointillist painters and employ them to create rendering algorithm that generates images in a pointillist style. We determine the distribution of colors in several paintings by Seurat and quantify a number of the theory that he employs. Using an RYB color wheel and a hierarchical point generation technique, we convert an input image into a set of colored dots, which is again converted into brush strokes with appropriate shapes and directions. We present images which illustrate the extent to which we have managed to simulate Seurat’s technique.

Efficient paper mosaic rendering on mobile devices based on position-based tiling

According to the growth of mobile technology, people experience high-performance mobile devices. In this environment, processing in real-time is required for mobile application. For colored paper mosaic application on mobile devices, the problem regarding speed must be solved while maintaining high-quality. In this paper, we propose an accelerated method that generates tiles based on their position. We locate tiles by considering the edges of the image and the shapes of neighbor tiles. The shape of the tiles is determined based on the position of each tile. In addition, we display the generation process of a result for our method be seemed real-time method. In here, we propose an ordering method that is similar to the ordering method of humans by considering color, edge, distance and direction.

Painterly rendering with designed imperfection

Even a highly skilled painter is unable to predict all the events that may occur on a canvas. As a result, a painter’s eyes, hands, and brain continue to make errors; and although the sum of the errors is often adverse to the intention of the artist, it frequently becomes a chance to create unique expression. The process of adaptation to obstacles and subjugation by inevitable restrictions (material, skill...etc) are what make paintings more humane and beautiful. We assumed these to be the core systems of a human being’s painting process.

The Decorative PixMosaics: Using Directional Photo Tiles

This paper introduces a new kind of mosaic, called the Decorative PixMosaic, where photo tiles of square shapes are used to compose the final image. We can express the resulting image with a similar color distribution of input images from small photo tiles. Based on an input image, user-selected edge features and a wide range of photo tiles, the method can both reproduce the image’s textures and emphasize the selected edges by placing tiles that follow the edges. The voronoi site is situated in the center point of the tile using the Centroidal Voronoi Diagram for equally maintaining the distance among the tiles. To express the edges using tiles on the voronoi site as the center point, tiles do not cross image edges and are drawn up as following edge’s direction. We use a distribution photo with similar color selected from the photo database. It is important to search for a visually similar photo. Hence we must have a large number of photo tiles.

A multi-level depiction method for painterly rendering based on visual perception cue

Increasing the level of detail (LOD) in brushstrokes within areas of interest improved the realism of painterly rendering. Using a modified quad-tree, we segmented an image into areas with similar levels of saliency; each of these segments was then used to control the brush strokes during rendering. We could also simulate real oil painting steps based on saliency information. Our method runs in a reasonable fine and produces results that are visually appealing and competitive with previous techniques.

Generation of coherent mosaic animations: enhancement and evaluation of temporal coherence

Although the creation static mosaic‐like images from non‐mosaic input has been studied, satisfactory methods to maintain and evaluate the temporal coherence of tiles for mosaic animations have remained elusive. Here, we describe a method that successfully generates mosaic animations from videos by applying a temporally and spatially coherent tile‐arrangement technique. We arrange tiles on the basis of the feature lines extracted from video input. We then animate the tiles along the motion of the video, add and delete tiles to preserve the tile density, and smooth tile color via frames. Finally, we propose indices to evaluate the temporal coherence of video‐based animations, and show that our animations are temporally coherent. Copyright

A painterly rendering based on stroke profile and database

We present a method for producing painting-like images composed of predefined brush strokes. Our proposed method is based on image retrieval method and uses a stroke database. The stroke database consists of transformed copies of the several brush stroke profiles which are obtained from an actual brush stroke. An input image can be reordered in a painterly manner by combination of brush strokes retrieved from the database. Our method is able to produce a painting with diverse media by changing the type of database, such as oil and pastel. In this process, we present a search algorithm to select an appropriate brush stroke from database and an assessment algorithm to judge whether to draw the retrieved brush stroke on the canvas or not. We also introduce a efficient brush stroke model and way of achieving the appearance of thick paint without physical simulation.