Yingying She

A Real-Time Hand Gesture Recognition Approach Based on Motion Features of Feature Points

Dynamic hand gesture recognition enables people to communicate with computers naturally without any mechanical devices. Due to the spread of depth sensor such as Microsoft Kinect and Leap Motion, dynamic hand gesture recognition becomes possible for recognizing meticulous gesture information in real time. However, most of these methods recognize the hand gesture by fuzzy features such as contour size, which cause imprecise hand gesture recognition. This paper presents a precise tracing of feature points including palm center, fingertips and joints by using Kinect. A novel recognition method based on precise motion features of these feature points is also presented. Having been tested with a series of applications, our method is proved to be robust and effective, and suitable for further application in real-time HCI systems.

An implicit skeleton-based method for the geometry reconstruction of vasculatures

Due to the high complexity of vascular system network, the geometry reconstruction of vasculatures from raw medical datasets remains a very challenging task. In this paper, we present a novel skeleton-based method for the geometry reconstruction of vascular structures from standard 3D medical datasets. With the proposed techniques, the geometry of vascular structures with high level of smoothness and accuracy can be reconstructed from the raw medical datasets. The experimental results and comparison with other techniques demonstrate that our method can achieve faithful and smooth vascular structures. In addition, quantitative validation has been conducted to evaluate the accuracy and smoothness of the reconstructed vessel geometry based on the proposed method.

Realistic and stable animation of cloth

Researchers have proposed various techniques for cloth simulation in the last decades. The crucial problem in interactive animation for cloth is how to speed up simulation with a stable system. In this paper, we describe a realistic and stable scheme for cloth simulation based on mass‐spring system. This scheme modifies semi‐implicit integration used in cloth simulation system with an efficient damping method. Semi‐implicit integration methods have been widely used in dynamic simulation because of acceptable speed and stability. However, internal damping forces are generated with respect to rotational rigid motions, which are only depending on relative velocities. Undesirable change in global movement of dynamic cloth could result in damping artifact. We replace the internal damping forces with an optimal damping method which is based on iterative spring damping but the limit can be computed directly. The method provides simple damping parameter estimation and guarantees conservation of global movement. As a result, complex clothes can be realistically and stably simulated in real time. Copyright

A Procedural Planning System for Goal Oriented Agents in Games

This paper explores a procedural planning system for the control of game agents in real time. The planning methodology we present is based on offline goal-oriented behavioral design, and is implemented as a procedural planning system in real-time. Our design intends to achieve efficiency of planning in order to have smooth run-time animation generation. Our experimental results show that the approach is capable of improving agent control for real-time goal processing in games.

Integrated Approach of Dynamic Human Eye Movement Recognition and Tracking in Real Time

The states and movements of human eyes contain a lot of useful information, in which can be applied in real-time HCI systems. This paper introduces an integrated human eye movement recognition and tracking approach. The threshold based eye recognition method identifies eye elements, such as iris and pupils of human eyes. In addition, the eye movement tracking method is present by analyses motion feature of eyes including translation and velocity. In experiments, real-time tests of different peoples eyes recognition and tracking are present, and NUI based application scenarios is designed to show the potential application of eye interaction systems.

The potential relationship discovery model based on result fusion for biomedical medicine research

With the amount of biomedical data growing explosively, medical scientists use many datasets in research for new medicine. However, the amount of biomedical data is growing too fast to abstract hidden information. At the same time, with the development of data storage diversification, scientists prefer to have data fusion based on heterogeneous data sources as opposed to a single data source, and ultimately to achieve knowledge and discovery across heterogeneous databases. Our study focuses on extending the application of latent semantic analysis methodologies into the area of biomedical research. Our purpose is to develop a model for discovering potential relationships between medicines and diseases based on biomedical latent semantic analysis. This model could be used in constructing link maps for biomedical entities, and provide a theoretical basis and practical support for biomedical scientists in their study of the disease–medicine relationship. In detail, we discuss the study of the integration of the latent semantic analysis model and data fusion methodologies. Our result fusion solution combines scientific literature repositories and a biomedical database based on context and the ABC model, and is supervised by a semi-supervised learning algorithm and data fusion algorithms. The expectation is that fused data could represent multilevel potential relationships between biological entities and related emotional relationship expression. The model is validated by experience and proven to be feasible and effective.