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排序方式: 共有9308条查询结果,搜索用时 39 毫秒
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Chiung Ching Ho Hu Ng Wooi-Haw Tan Kok-Why Ng Hau-Lee Tong Timothy Tzen-Vun Yap Pei-Fen Chong C. Eswaran Junaidi Abdullah 《Pattern recognition letters》2013
This paper describes the baseline corpus of a new multimodal biometric database, the MMU GASPFA (Gait–Speech–Face) database. The corpus in GASPFA is acquired using commercial off the shelf (COTS) equipment including digital video cameras, digital voice recorder, digital camera, Kinect camera and accelerometer equipped smart phones. The corpus consists of frontal face images from the digital camera, speech utterances recorded using the digital voice recorder, gait videos with their associated data recorded using both the digital video cameras and Kinect camera simultaneously as well as accelerometer readings from the smart phones. A total of 82 participants had their biometric data recorded. MMU GASPFA is able to support both multimodal biometric authentication as well as gait action recognition. This paper describes the acquisition setup and protocols used in MMU GASPFA, as well as the content of the corpus. Baseline results from a subset of the participants are presented for validation purposes. 相似文献
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Chong Lin Qing-Guo Wang Tong Heng Lee Yong He Bing Chen 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2007,37(4):1030-1038
This correspondence studies the problem of observer-based H infinity control for time-delay Takagi-Sugeno (T-S) fuzzy systems. It provides a delay-dependent linear matrix inequality (LMI)-based method for the control design. It is known that the key important problem in the literature, even for delay-independent case, lies in the difficulty of decoupling matrix variables in corresponding matrix inequalities. This correspondence suggests a decoupling technique for solving matrix inequalities with coupled variables, and provides an LMI-based algorithm by adopting the idea of the cone complementarity problem. The derivation relies on the appropriate choice of Lyaponuv-Krasovskii functionals which incorporate the intersections among local systems. Illustrative examples are given to show the effectiveness of the present delay-dependent result. 相似文献
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Portrait-background image composition is a widely used operation in selfie editing, video meeting, and other portrait applications. To guarantee the realism of the composited images, the appearance of the foreground portraits needs to be adjusted to fit the new background images. Existing image harmonization approaches are proposed to handle general foreground objects, thus lack the special ability to adjust portrait foregrounds. In this paper, we present a novel end-to-end network architecture to learn both the content features and style features for portrait-background composition. The method adjusts the appearance of portraits to make them compatible with backgrounds, while the generation of the composited images satisfies the prior of a style-based generator. We also propose a pipeline to generate high-quality and high-variety synthesized image datasets for training and evaluation. The proposed method outperforms other state-of-the-art methods both on the synthesized dataset and the real composited images and shows robust performance in video applications. 相似文献
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