Browsing by Author "Lee, Tong-Yee"

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Geometric and Textural Blending for 3D Model Stylization
(2018-02-01)
Huang, Yi-Jheng
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Lin, Wen-Chieh
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Yeh, I-Cheng
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Lee, Tong-Yee
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資訊工程學系
Stylizing a 3D model with characteristic shapes or appearances is common in product design, particularly in the design of 3D model merchandise, such as souvenirs, toys, furniture, and stylized items. A model stylization approach is proposed in this study. The approach combines base and style models while preserving user-specified shape features of the base model and the attractive features of the style model with limited assistance from a user. The two models are first combined at the topological level. A tree-growing technique is utilized to search for all possible combinations of the two models. Second, the models are combined at textural and geometric levels by employing a morphing technique. Results show that the proposed approach generates various appealing models and allows users to control the diversity of the output models and adjust the blending degree between the base and style models. The results of this work are also experimentally compared with those of a recent work through a user study. The comparison indicates that our results are more appealing, feature-preserving, and reasonable than those of the compared previous study. The proposed system allows product designers to easily explore design possibilities and assists novice users in creating their own stylized models.
Real-Time Physics-Based 3D Biped Character Animation Using an Inverted Pendulum Model
(2010-03-01)
Tsai, Yao-Yang
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Lin, Wen-Chieh
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Cheng, Kuangyou B.
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Lee, Jehee
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Lee, Tong-Yee
We present a physics-based approach to generate 3D biped character animation that can react to dynamical environments in real time. Our approach utilizes an inverted pendulum model to online adjust the desired motion trajectory from the input motion capture data. This online adjustment produces a physically plausible motion trajectory adapted to dynamic environments, which is then used as the desired motion for the motion controllers to track in dynamics simulation. Rather than using Proportional-Derivative controllers whose parameters usually cannot be easily set, our motion tracking adopts a velocity-driven method which computes joint torques based on the desired joint angular velocities. Physically correct full-body motion of the 3D character is computed in dynamics simulation using the computed torques and dynamical model of the character. Our experiments demonstrate that tracking motion capture data with real-time response animation can be achieved easily. In addition, physically plausible motion style editing, automatic motion transition, and motion adaptation to different limb sizes can also be generated without difficulty.
Scalable and Coherent Video Resizing with Per-Frame Optimization
(2011-07-01)
Wang, Yu-Shuen
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Hsiao, Jen-Hung
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Sorkine, Olga
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Lee, Tong-Yee
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交大名義發表
The key to high-quality video resizing is preserving the shape and motion of visually salient objects while remaining temporally-coherent. These spatial and temporal requirements are difficult to reconcile, typically leading existing video retargeting methods to sacrifice one of them and causing distortion or waving artifacts. Recent work enforces temporal coherence of content-aware video warping by solving a global optimization problem over the entire video cube. This significantly improves the results but does not scale well with the resolution and length of the input video and quickly becomes intractable. We propose a new method that solves the scalability problem without compromising the resizing quality. Our method factors the problem into spatial and time/motion components: we first resize each frame independently to preserve the shape of salient regions, and then we optimize their motion using a reduced model for each pathline of the optical flow. This factorization decomposes the optimization of the video cube into sets of sub-problems whose size is proportional to a single frame's resolution and which can be solved in parallel. We also show how to incorporate cropping into our optimization, which is useful for scenes with numerous salient objects where warping alone would degenerate to linear scaling. Our results match the quality of state-of-the-art retargeting methods while dramatically reducing the computation time and memory consumption, making content-aware video resizing scalable and practical.
Social-Event-Driven Camera Control for Multicharacter Animations
(2012-09-01)
Yeh, I-Cheng
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Lin, Wen-Chieh
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Lee, Tong-Yee
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Han, Hsin-Ju
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Lee, Jehee
"In a virtual world, a group of virtual characters can interact with each other, and these characters may leave a group to join another. The interaction among individuals and groups often produces interesting events in a sequence of animation. The goal of this paper is to discover social events involving mutual interactions or group activities in multicharacter animations and automatically plan a smooth camera motion to view interesting events suggested by our system or relevant events specified by a user. Inspired by sociology studies, we borrow the knowledge in Proxemics, social force, and social network analysis to model the dynamic relation among social events and the relation among the participants within each event. By analyzing the variation of relation strength among participants and spatiotemporal correlation among events, we discover salient social events in a motion clip and generate an overview video of these events with smooth camera motion using a simulated annealing optimization method. We tested our approach on different motions performed by multiple characters. Our user study shows that our results are preferred in 66.19 percent of the comparisons with those by the camera control approach without event analysis and are comparable (51.79 percent) to professional results by an artist."
Spatially and Temporally Optimized Video Stabilization
(2013-08-01)
Wang, Yu-Shuen
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Liu, Feng
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Hsu, Pu-Sheng
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Lee, Tong-Yee
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資訊工程學系
Properly handling parallax is important for video stabilization. Existing methods that achieve the aim require either 3D reconstruction or long feature trajectories to enforce the subspace or epipolar geometry constraints. In this paper, we present a robust and efficient technique that works on general videos. It achieves high-quality camera motion on videos where 3D reconstruction is difficult or long feature trajectories are not available. We represent each trajectory as a Bezier curve and maintain the spatial relations between trajectories by preserving the original offsets of neighboring curves. Our technique formulates stabilization as a spatial-temporal optimization problem that finds smooth feature trajectories and avoids visual distortion. The Bezier representation enables strong smoothness of each feature trajectory and reduces the number of variables in the optimization problem. We also stabilize videos in a streaming fashion to achieve scalability. The experiments show that our technique achieves high-quality camera motion on a variety of challenging videos that are difficult for existing methods.
Stylized rendering using samples of a painted image
(2008-03-01)
Yan, Chung-Ren
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Chi, Ming-Te
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Lee, Tong-Yee
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Lin, Wen-Chieh
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資訊工程學系
We introduce a novel technique to generate painterly art maps (PAMs) for 3D nonphotorealistic rendering. Our technique can automatically transfer brushstroke textures and color changes to 3D models from samples of a painted image. Therefore, the generation of stylized images or animation in the style of a given artwork can be achieved. This new approach works particularly well for a rich variety of brushstrokes ranging from simple 1D and 2D line-art strokes to very complicated ones with significant variations in stroke characteristics. During the rendering or animation process, the coherence of brushstroke textures and color changes over 3D surfaces can be well maintained. With PAM, we can also easily generate the illusion of flow animation over a 3D surface to convey the shape of a model.