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Your search keyword '"Philip Chen, Chun Lung"' showing total 6 results
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6 results on '"Philip Chen, Chun Lung"'

2. Recognizing complex events in real movies by combining audio and video features

Author

Philip Chen Chun Lung, Ji-Xiang Du, Chuan-Min Zhai, Yi-Lan Guo, and Yuan Yan Tang

Subjects
Support vector machine, Artificial Intelligence, Computer science, Event (computing), business.industry, Cognitive Neuroscience, Shot (filmmaking), Speech recognition, Feature (machine learning), Pattern recognition, Artificial intelligence, business, Computer Science Applications
Abstract

This paper proposes a novel approach in taking audio feature into account for better event recognition performance in recognizing complex events in real movies, since audio can provide strong evidence to certain events. In our method, local-space time feature and audio feature are firstly extracted from the video sequences and then an individual video sequence is represented as a SOFM density map; finally we integrate such density map with SVM for recognition events. To evaluate effectiveness of this method, this paper uses the public Hollywood dataset, in this dataset the shot sequences have been collected from 32 different Hollywood movies and it includes 8 event classes. The presented result justifies the proposed method explicitly, improve the average accuracy and average precision compared to other relative approaches.

Published
2014

6. Robust Adaptive Fuzzy Control of Nonlinear Systems with Unknown and Time-Varying Saturation.

Author

Lai, Guanyu, Liu, Zhi, Zhang, Yun, Chen, Xin, and Philip Chen, Chun Lung

Subjects
FUZZY control systems, ADAPTIVE fuzzy control, STABILITY of nonlinear systems, MAGNETIZATION transfer, TIME series analysis
Abstract

In this paper, a robust adaptive fuzzy control approach is proposed for a class of nonlinear systems in strict-feedback form with the unknown time-varying saturation input. To deal with the time-varying saturation problem, a novel controller separation approach is proposed in the literature to separate the desired control signal from the practical constrained control input. Furthermore, an optimized adaptation method is applied to the dynamic surface control design to reduce the number of adaptive parameters. By utilizing the Lyapunov synthesis, the fuzzy logic system technique and the Nussbaum function technique, an adaptive fuzzy control algorithm is constructed to guarantee that all the signals in the closed-loop control system remain semiglobally uniformly ultimately bounded, and the tracking error is driven to an adjustable neighborhood of the origin. Finally, some numerical examples are provided to validate the effectiveness of the proposed control scheme in the literature. [ABSTRACT FROM AUTHOR]

Published
2015
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