25,973 research outputs found

    Real-time motion data annotation via action string

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    Even though there is an explosive growth of motion capture data, there is still a lack of efficient and reliable methods to automatically annotate all the motions in a database. Moreover, because of the popularity of mocap devices in home entertainment systems, real-time human motion annotation or recognition becomes more and more imperative. This paper presents a new motion annotation method that achieves both the aforementioned two targets at the same time. It uses a probabilistic pose feature based on the Gaussian Mixture Model to represent each pose. After training a clustered pose feature model, a motion clip could be represented as an action string. Then, a dynamic programming-based string matching method is introduced to compare the differences between action strings. Finally, in order to achieve the real-time target, we construct a hierarchical action string structure to quickly label each given action string. The experimental results demonstrate the efficacy and efficiency of our method

    Comments on event driven animation

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    Event driven animation provides a general method of describing controlling values for various computer animation techniques. A definition and comments are provided on genralizing motion description with events. Additional comments are also provided about the implementation of twixt

    A semantic feature for human motion retrieval

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    With the explosive growth of motion capture data, it becomes very imperative in animation production to have an efficient search engine to retrieve motions from large motion repository. However, because of the high dimension of data space and complexity of matching methods, most of the existing approaches cannot return the result in real time. This paper proposes a high level semantic feature in a low dimensional space to represent the essential characteristic of different motion classes. On the basis of the statistic training of Gauss Mixture Model, this feature can effectively achieve motion matching on both global clip level and local frame level. Experiment results show that our approach can retrieve similar motions with rankings from large motion database in real-time and also can make motion annotation automatically on the fly. Copyright © 2013 John Wiley & Sons, Ltd

    Human motion retrieval based on freehand sketch

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    In this paper, we present an integrated framework of human motion retrieval based on freehand sketch. With some simple rules, the user can acquire a desired motion by sketching several key postures. To retrieve efficiently and accurately by sketch, the 3D postures are projected onto several 2D planes. The limb direction feature is proposed to represent the input sketch and the projected-postures. Furthermore, a novel index structure based on k-d tree is constructed to index the motions in the database, which speeds up the retrieval process. With our posture-by-posture retrieval algorithm, a continuous motion can be got directly or generated by using a pre-computed graph structure. What's more, our system provides an intuitive user interface. The experimental results demonstrate the effectiveness of our method. © 2014 John Wiley & Sons, Ltd

    Interactions around a contextually embedded system

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    This paper discusses observations of visitor interactions around a museum installation, focusing on how physical setup and shape of two variants of the installation, a telescope-like viewer and a barrier-free screen, shaped visitor experiences and interactions around and with the system. The analysis investigates contextual embedding, and how the two system variants affected people's ability of sharing the experience and negotiating use

    An Investigation into Animating Plant Structures within Real-time Constraints

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    This paper is an analysis of current developments in rendering botanical structures for scientic and entertainment purposes with a focus on visualising growth. The choices of practical investigations produce a novel approach for parallel parsing of difficult bracketed L-Systems, based upon the work of Lipp, Wonka and Wimmer (2010). Alongside this is a general overview of the issues involved when looking at growing systems, technical details involving programming for the Graphics Processing Unit (GPU) and other possible solutions for further work that also could achieve the project's goals

    A Framework for Active Learning: Revisited

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    Over the past decade, algorithm visualization tools have been researched and developed to be used by Computer Science instructors to ease students’ learning curve for new concepts. However, limitations such as rigid animation frameworks, lack of user interaction with the visualization created, and learning a new language and environment, have severely reduced instructors’ desire to use such a tool. The purpose of this project is to create a tool that overcomes these limitations. Instructors do not have to get familiar with a new framework and learn another language. The API used to create algorithm animation for this project is through Java, a programming language familiar to many instructors. Moreover, not only do the instructors have control over planning the animation, students using the animation will also have the ability to interact with it
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