This paper introduces an Augmented Reality system recognizing hand gestures and shows results of the evaluation. The system's user can interact with artificial objects and manipulate their position and motions simply by his hand gestures. Hand gesture recognition is based on Histograms of Oriented Gradients (HOG). Salient features of human hand appearance are detected by HOG blocks. Blocks of different sizes are tested to define the most suitable configuration. To select the most informative blocks for classification multiclass AdaBoostSVM algorithm is applied. Evaluated recognition rate of the algorithm is 94.0%.
Multimedia documents can be transferred quickly and easily across the Internet, and has attracted considerable interest in multimedia security and multimedia copyright protection. This paper proposes an animage watermarking scheme embedding a binary watermark image using Discrete Wavelet Transform (DWT) coefficients. The original image is transformed to the wavelet domain and decomposed in subbands. The binary watermark image, as a sequence of bits, is embedded into the middle frequency subbands. The original image is not needed to detect the watermark image. The proposed method detected fewer watermark bits but produced an approximately 10dB higher PSNR than the max/min method.
This paper reports the direct controller for nonlinear plants using a neural network. The controller was composed of an approximate controller and a neural network auxiliary controller. The approximate controller provides rough control and the neural network controller gives the complementary signal to further reduce the output tracking error. This method does not place too much restriction on the type of nonlinear plant to be controlled. In this method, a RBF neural network was trained and the system showed stable performance for the inputs it has been trained for. The simulation results showed that it was quite effective and could realize satisfactory control of the nonlinear system.
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