Current Issue : January - March Volume : 2014 Issue Number : 1 Articles : 4 Articles
A novel model of image segmentation based on watershed method is proposed in this paper. To prevent the oversegmentation of\r\ntraditional watershed, our proposed algorithm has five stages. Firstly, the morphological reconstruction is applied to smooth the flat\r\narea and preserve the edge of the image. Secondly, multiscale morphological gradient is used to avoid the thickening and merging\r\nof the edges. Thirdly, for contrast enhancement, the top/bottomhat transformation is used. Fourthly, the morphological gradient of\r\nan image is modified by imposing regional minima at the location of both the internal and the external markers. Finally, a weighted\r\nfunction is used to combine the top/bottomhat transformation algorithmand themarkers algorithmto get the new algorithm. The\r\nexperimental results show the superiority of the new algorithm in terms of suppression over-segmentation....
This work relates to the regions-of-interest (ROI) coding that is a desirable feature in future applications based on the scalable video\r\ncoding, which is an extension of the H.264/MPEG-4 AVC standard. Due to the dramatic technological progress, there is a plurality\r\nof heterogeneous devices, which can be used for viewing a variety of video content. Devices such as smartphones and tablets\r\nare mostly resource-limited devices, which make it difficult to display high-quality content. Usually, the displayed video content\r\ncontains one or more ROI(s), which should be adaptively selected from the preencoded scalable video bitstream.Thus, an efficient\r\nscalable ROI video coding scheme is proposed in this work, thereby enabling the extraction of the desired regions-of-interest and\r\nthe adaptive setting of the desirable ROI location, size, and resolution. In addition, an adaptive bit-rate control is provided for the\r\nregion-of-interest scalable video coding.Theperformance of the presented techniques is demonstrated and compared with the joint\r\nscalable video model reference software (JSVM 9.19), thereby showing significant bit-rate savings as a tradeoff for the relatively low\r\nPSNR degradation....
We describe the design of a system consisting of several state-of-the-art real-time audio and video processing components\r\nenabling multimodal stream manipulation (e.g., automatic online editing for multiparty videoconferencing applications) in open,\r\nunconstrained environments. The underlying algorithms are designed to allow multiple people to enter, interact, and leave the\r\nobservable scene with no constraints. They comprise continuous localisation of audio objects and its application for spatial audio\r\nobject coding, detection, and tracking of faces, estimation of head poses and visual focus of attention, detection and localisation\r\nof verbal and paralinguistic events, and the association and fusion of these different events. Combined all together, they represent\r\nmultimodal streams with audio objects and semantic video objects and provide semantic information for stream manipulation\r\nsystems (like a virtual director). Various experiments have been performed to evaluate the performance of the system.Theobtained\r\nresults demonstrate the effectiveness of the proposed design, the various algorithms, and the benefit of fusing different modalities\r\nin this scenario....
Due to the widening semantic gap of videos, computational tools to classify these videos into different genre are highly needed to\r\nnarrow it. Classifying videos accurately demands good representation of video data and an efficient and effective model to carry\r\nout the classification task. Kernel Logistic Regression (KLR), kernel version of logistic regression (LR), proves its efficiency as a\r\nclassifier, which can naturally provide probabilities and extend tomulticlass classification problems. In this paper,Weighted Kernel\r\nLogistic Regression (WKLR) algorithm is implemented for video genre classification to obtain significant accuracy, and it shows\r\naccurate and faster good results....
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