Shujin Lin

A combined approximating and interpolating subdivision scheme with C 2 continuity

Abstract In this paper a combined approximating and interpolating subdivision scheme is presented. The relationship between approximating subdivision and interpolating subdivision is derived by directly performing operations on geometric rules. The behavior of the limit curve produced by our combined subdivision scheme is analyzed by the Laurent polynomial and attains C 2 degree of smoothness. Furthermore, a non-uniform combined subdivision with shape control parameters is introduced, which allows a different tension value for every edge of the original control polygon.

Interpolatory and Mixed Loop Schemes

This paper presents a new interpolatory Loop scheme and an unified and mixed interpolatory and approximation subdivision scheme for triangular meshes. The former which is C1 continuous as same as the modified Butterfly scheme has better effect in some complex models. The latter can be used to solve the “popping effect” problem when switching between meshes at different levels of resolution. The scheme generates surfaces coincident with the Loop subdivision scheme in the limit condition having the coefficient k equal 0. When k equal 1, it will be changed into a new interpolatory subdivision scheme. Eigen‐structure analysis demonstrates that subdivision surfaces generated using the new scheme are C1 continuous. All these are achieved only by changing the value of a parameter k. The method is a completely simple one without constructing and solving equations. It can achieve local interpolation and solve the “popping effect” problem which are the methods advantages over the modified Butterfly scheme.

A 3D model perceptual feature metric based on global height field

Human visual attention system tends to be attracted to perceptual feature points on 3D model surfaces. However, purely geometric-based feature metrics may be insufficient to extract perceptual features, because they tend to detect local structure details. Intuitively, the perceptual importance degree of vertex is associated with the height of its geometry position between original model and a datum plane. So, we propose a novel and straightforward method to extract perceptually important points based on global height field. Firstly, we construct spectral domain using Laplace–Beltrami operator, and we perform spectral synthesis to reconstruct a rough approximation of the original model by adopting low-frequency coefficients, and make it as the 3D datum plane. Then, to build global height field, we calculate the Euclidean distance between vertex geometry position on original surface and the one on 3D datum plane. Finally, we set a threshold to extract perceptual feature vertices. We implement our technique on several 3D mesh models and compare our algorithm to six state-of-the-art interest points detection approaches. Experimental results demonstrate that our algorithm can accurately capture perceptually important points on arbitrary topology 3D model.

Coupling deep correlation filter and online discriminative learning for visual object tracking

Advances in mathematical models and optimization introduce powerful tools for solving the visual object tracking problem, but this fundamental problem remains unsolved due to various challenges such as illumination variation, deformation and occlusion. Recent progress in correlation filter based models has provided an effective and efficient tracking solution. This type of trackers exploits the property of convolution theorem to significantly speed up their computational processes. However, their scheme of training correlation filters restricts them to use only a few negative examples to train their model, consequently lowers their performance. Therefore, in this paper, we propose to combine the fast calculation advantage of correlation filter with an online discriminative learning model, which can fully exploit the negative examples in the context around the target. The proposed tracker proceeds in a coarse-to-fine scheme: the proposed tracker will first employ a correlation filter to generate a coarse estimation of the location of the target, and then employ a translating model to refine its estimation and calculate the scale variation of the target via a scaling model. Both the translating model and the scaling model are formulated in the framework of our online discriminative model. Besides, we also propose an effective offline representation learning method to generate robust image feature for our correlation filter. Extensive experiments on the online Object Tracking Benchmark against the state-of-the-art methods validate the effectiveness of the proposed tracker.

A Novel System for Visual Navigation of Educational Videos Using Multimodal Cues

With recent developments and advances in distance learning and MOOCs, the amount of open educational videos on the Internet has grown dramatically in the past decade. However, most of these videos are lengthy and lack of high-quality indexing and annotations, which triggers an urgent demand for efficient and effective tools that facilitate video content navigation and exploration. In this paper, we propose a novel visual navigation system for exploring open educational videos. The system tightly integrates multimodal cues obtained from the visual, audio and textual channels of the video and presents them with a series of interactive visualization components. With the help of this system, users can explore the video content using multiple levels of details to identify content of interest with ease. Extensive experiments and comparisons against previous studies demonstrate the effectiveness of the proposed system.

Distortion-Aware Correlation Tracking

Recently, correlation filter (CF)-based tracking methods have attracted considerable attention because of their high-speed performance. However, distortion, which refers to the phenomenon that the correlation outputs of CF-based trackers are distorted, remains a major obstacle for these methods. In this paper, we propose a distortion-aware correlation filter framework, which can detect distortions and recover from tracking failures. Our framework employs a simple yet effective feature termed normed correlation response to detect distortions. Meanwhile, we introduce a competition mechanism to handle distortions, in which we build a specialized graph to formulate and handle tracking under distortion as a maximum multi clique problem. Furthermore, a global-local context model is exploited to alleviate underlying distortions during the tracking process. Extensive experiments on the Online Tracking Benchmark show that our tracker can find the optimal target trajectory during the distortion period and retrieve the possibly missing target, consequently outperforms the state-of-the-art methods and improves the performance of CF-based trackers favorably.Recently, correlation filter (CF)-based tracking methods have attracted considerable attention because of their high-speed performance. However, distortion, which refers to the phenomenon that the correlation outputs of CF-based trackers are distorted, remains a major obstacle for these methods. In this paper, we propose a distortion-aware correlation filter framework, which can detect distortions and recover from tracking failures. Our framework employs a simple yet effective feature termed normed correlation response to detect distortions. Meanwhile, we introduce a competition mechanism to handle distortions, in which we build a specialized graph to formulate and handle tracking under distortion as a maximum multi clique problem. Furthermore, a global-local context model is exploited to alleviate underlying distortions during the tracking process. Extensive experiments on the Online Tracking Benchmark show that our tracker can find the optimal target trajectory during the distortion period and retrieve the possibly missing target, consequently outperforms the state-of-the-art methods and improves the performance of CF-based trackers favorably.

A novel 3D model retrieval system based on three-view sketches

© 2016 - IOS Press and the authors. All rights reserved.3D models can be used in 3D printing and many other areas. At present, there are a lot of researches on 3D model retrieval and sketch is considered to be important for 3D model retrieval. In this paper, we develop a new 3D model retrieval prototype system based on style-sensitive 3D model retrieval method and three-view user sketches. We also implement user-friendly graphic interfaces for the 3D model retrieval system. We explore the performance of the system by conducting a series of 3D model retrieval experiments on the Princeton shape benchmark data set. Experimental results show that the new retrieval system can obtain satisfactory retrieval results. And some results of the new method are superior to some content-based 3D model retrieval methods, in terms of both quantitative search performance metrics and qualitatively measured user search experiences.

A Method for Deducing Interpolating Subdivision Schemes from Approximating Subdivision Schemes and Blending Subdivisions

We present a method for deducing interpolating subdivision schemes from known approximating subdivision scheme which generates curves and blending subdivision schemes. We make use of the connection between the approximating subdivision schemes and interpolating subdivision schemes to produce a blending subdivision scheme that integrates interpolating and approximating subdivision schemes in a simple and efficient way. The basic idea is to use the specific linear combination of the displacements of the new vertices which are derived from approximating subdivision scheme to produce associated interpolating displacements for the new vertices therefore generating a corresponding interpolating subdivision scheme. The most importance is that such methods are deduced in premise of keeping the continuity of the original approximating subdivision schemes. In addition, our method has much lower computational complexity compared with the exiting methods and can be easily extended to the case of surface subdivision schemes. Keywords-interpolating subdivision, approximating subdivision, continuity

Improving incompressible SPH simulation efficiency by integrating density-invariant and divergence-free conditions

Our method shortens the time of fluid simulation by coupling the two conditions of density-invariant and divergence-free, and achieves the same simulation effect compared with other methods. Further, we regard the displacement of particles as the only basic variable of the continuity equation, which improves the stability of the fluid to a certain extent.

A novel approach to automatic detection of presentation slides in educational videos

Recent advancement in learning and teaching methodology experimented with virtual reality (VR)-based presentation form to create immersive learning and training environment. The quality of such educational VR applications not only relies on the virtual model, but the 2D presentation materials such as text, diagrams and figures. However, manual designing or seeking these educational resources is both labor intensive and time-consuming. In this paper, we introduce a new automatic algorithm to detect and extract presentation slides in educational videos, which will provide abundant resources for creating slide-based immersive presentation environment. The proposed approach mainly involves five core components: shot boundary detection, training instances collection, shot classification, slide region detection and slide transition detection. We conducted comparison experiment to evaluate the performance of the proposed method. The results indicate that, in comparison with peer method, the proposed method improves the precision of slide detection from 81.6 to 92.6% and recall from 74.7 to 86.3% on average. With the detected slides, content analyzer can be employed to further extract reusable elements, which can be used for developing VR-based educational applications.