Browsing by Author "Chang, Chin-Chen"

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Adaptive sampling approach for volumetric shadows in dynamic scenes
(2013-11-01)
Lin, Hsiang-Yu
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Chang, Chin-Chen
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Tsai, Yu-Ting
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Way, Der-Lor
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Shih, Zen-Chung
Ray marching is an important technique to generate volumetric lighting effects. However, it is very expensive for each pixel on the screen, especially in dynamic scenes. The authors propose an adaptive approach to reduce samples for volumetric shadows in the time domain. In dynamic scenes, shadow volumes of moving objects are created and are rasterised to decide pixels that cannot be reused. The authors use a stencil buffer to maintain the information of screen pixels by recomputing or just using the previous information. Experimental results show that the proposed approach is simple to implement. Moreover, compared to the previous method, the proposed approach achieves a specific speedup and maintains similar visual quality.
An Efficient Structure-Aware Bilateral Texture Filtering for Image Smoothing
(2016-10-01)
Lin, Ting-Hao
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Way, Der-Lor
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Shih, Zen-Chung
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Tai, Wen-Kai
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Chang, Chin-Chen
Photos contain well-structured and plentiful visual information. Edges are active and expressive stimuli for human visual perception. However, it is hard to separate structure from details because edge strength and object scale are entirely different concepts. This paper proposes a structure-aware bilateral texture algorithm to remove texture patterns and preserve structures. Our proposed method is simple and fast, as well as effective in removing textures. Instead of patch shift, smaller patches represent pixels located at structure edges, and original patches represent the texture regions. Specifically, this paper also improves joint bilateral filter to preserve small structures. Moreover, a windowed inherent variation is adapted to distinguish textures and structures for detecting structure edges. Finally, the proposed method produces excellent experimental results. These results are compared to some results of previous studies. Besides, structure-preserving filtering is a critical operation in many image processing applications. Our proposed filter is also demonstrated in many attractive applications, such as seam carving, detail enhancement, artistic rendering, etc.
An Efficient Structure-Aware Bilateral Texture Filtering for Image Smoothing
(2016-10)
Lin, Ting-Hao
;
Way, Der-Lor
;
Shih, Zen-Chung
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Tai, Wen-Kai
;
Chang, Chin-Chen
Photos contain well-structured and plentiful visual information. Edges are active and expressive stimuli for human visual perception. However, it is hard to separate structure from details because edge strength and object scale are entirely different concepts. This paper proposes a structure-aware bilateral texture algorithm to remove texture patterns and preserve structures. Our proposed method is simple and fast, as well as effective in removing textures. Instead of patch shift, smaller patches represent pixels located at structure edges, and original patches represent the texture regions. Specifically, this paper also improves joint bilateral filter to preserve small structures. Moreover, a windowed inherent variation is adapted to distinguish textures and structures for detecting structure edges. Finally, the proposed method produces excellent experimental results. These results are compared to some results of previous studies. Besides, structure-preserving filtering is a critical operation in many image processing applications. Our proposed filter is also demonstrated in many attractive applications, such as seam carving, detail enhancement, artistic rendering, etc.
An Improved Style Transfer Approach for Videos
(2018-01-01)
Chang, Rong-Jie
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Chang, Chin-Chen
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Way, Der-Lor
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Shih, Zen -Chung
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資訊工程學系
In this paper, we present an improved approach to transfer style for videos based on semantic segmentation. We segment foreground objects and background, and then apply different styles respectively. A fully convolutional neural network is used to perform semantic segmentation. We increase the reliability of the segmentation, and use the information of segmentation and the relationship between foreground objects and background to improve segmentation iteratively. We also use segmentation to improve optical flow, and apply different motion estimation methods between foreground objects and background. This improves the motion boundaries of optical flow, and solves the problems of incorrect and discontinuous segmentation caused by occlusion and shape deformation.
Extending the Capture Volume of an Iris Recognition System Using Wavefront Coding and Super-Resolution
(2016-12)
Hsieh, Sheng-Hsun
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Li, Yung-Hui
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Tien, Chung-Hao
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Chang, Chin-Chen
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光電工程學系
Iris recognition has gained increasing popularity over the last few decades; however, the stand-off distance in a conventional iris recognition system is too short, which limits its application. In this paper, we propose a novel hardware-software hybrid method to increase the stand-off distance in an iris recognition system. When designing the system hardware, we use an optimized wavefront coding technique to extend the depth of field. To compensate for the blurring of the image caused by wavefront coding, on the software side, the proposed system uses a local patch-based super-resolution method to restore the blurred image to its clear version. The collaborative effect of the new hardware design and software post-processing showed great potential in our experiment. The experimental results showed that such improvement cannot be achieved by using a hardware-or software-only design. The proposed system can increase the capture volume of a conventional iris recognition system by three times and maintain the system\'s high recognition rate.
Generation of Stereo Images Based on a View Synthesis Network
(2020-05-01)
Lo, Yuan-Mau
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Chang, Chin-Chen
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Way, Der-Lor
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Shih, Zen-Chung
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多媒體工程研究所
The conventional warping method only considers translations of pixels to generate stereo images. In this paper, we propose a model that can generate stereo images from a single image, considering both translation as well as rotation of objects in the image. We modified the appearance flow network to make it more general and suitable for our model. We also used a reference image to improve the inpainting method. The quality of images resulting from our model is better than that of images generated using conventional warping. Our model also better retained the structure of objects in the input image. In addition, our model does not limit the size of the input image. Most importantly, because our model considers the rotation of objects, the resulting images appear more stereoscopic when viewed with a device.
GENETIC-BASED APPROACH FOR SYNTHESIZING TEXTURE
(2008-08-01)
Chang, Chin-Chen
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Kuo, Yen-Ting
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Tai, Wen-Kai
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多媒體工程研究所
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Institute of Multimedia Engineering
Intensive search schemes are commonly adopted in patched-based texture synthesis to identity the proper neighbors of each patch. However, they do not always provide perfect solutions. This work presents a genetic algorithm in evolutionary computation for patch-based texture synthesis. The representation of an input source texture is first adjusted. Then, the synthesizing result is generated and refined by the selection of individuals based on their fitness and executing crossover and mutation until the criteria are met. After the entire execution, a large output texture is generated with texture features similar to the source texture. Because this approach optimizes the genetic algorithm, the results are satisfactory.
Importance sampling of products from illumination and BRDF using spherical radial basis functions
(2008-07-01)
Tsai, Yu-Ting
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Chang, Chin-Chen
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Jiang, Qing-Zhen
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Weng, Shr-Ching
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資訊工程學系
In this paper, a new approach for the importance sampling of products from a complex high dynamic range (HDR) environment map and measured bidirectional reflectance distribution function (BRDF) data using spherical radial basis functions (SRBFs) is presented. In the pre-process, a complex HDR environment map and measured BRDF data are transformed into a scattered SRBF representation by using a non-uniform and non-negative SRBF fitting algorithm. An initial guess is determined for the fitting operation. In the run-time rendering process, after the product of the two SRBFs is evaluated, this is used to guide the number of samples. The sampling is done by mixing samples from the various "product" SRBFs using multiple importance sampling. Hence, the proposed approach efficiently renders images with multiple HDR environment maps and measured BRDFs.
Inner engraving for the creation of a balanced LEGO sculpture
(2016-05)
Hong, Jhen-Yao
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Way, Der-Lor
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Shih, Zen-Chung
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Tai, Wen-Kai
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Chang, Chin-Chen
LEGO is a globally popular toy composed of colorful interlocking plastic bricks that can be assembled in many ways; however, this special feature makes designing a LEGO sculpture particularly challenging. Building a stable sculpture is not easy for a beginner; even an experienced user requires a good deal of time to build one. This paper provides a novel approach to creating a balanced LEGO sculpture for a 3D model in any pose, using centroid adjustment and inner engraving. First, the input 3D model is transformed into a voxel data structure. Next, the model\'s centroid is adjusted to an appropriate position using inner engraving to ensure that the model stands stably. A model can stand stably without any struts when the center of mass is moved to the ideal position. Third, voxels are merged into layer-by-layer brick layout assembly instructions. Finally, users will be able to build a LEGO sculpture by following these instructions. The proposed method is demonstrated with a number of LEGO sculptures and the results of the physical experiments are presented.
Texture Tiling on 3D Models Using Automatic Polycube-maps and Wang Tiles
(2010-01-01)
Chang, Chin-Chen
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Lin, Chen-Yu
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資訊工程學系
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Department of Computer Science
In mapping textures onto 3D models, it is essential to eliminate all seams and avoid excessive distortions To achieve these goals, texture tiling provides an alternative approach for texturing surfaces In this paper, a texture tiling approach that combines polycube-maps and Wang tiles for 3D models is proposed The polycube of a 3D model is first constructed automatically and a tiling mechanism is then used to fill the tiles on the polycube Finally, rectangular cells which are transformed front the polycube are generated and textures are mapped onto the 3D model The results show that the proposed approach leads to seamless texture mapping on 3D models