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This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa. 相似文献
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In this paper we combine video compression and modern image processing methods. We construct novel iterative filter methods for prediction signals based on Partial Differential Equation (PDE) based methods. The mathematical framework of the employed diffusion filter class is given and some desirable properties are stated. In particular, two types of diffusion filters are constructed: a uniform diffusion filter using a fixed filter mask and a signal adaptive diffusion filter that incorporates the structures of the underlying prediction signal. The latter has the advantage of not attenuating existing edges while the uniform filter is less complex. The filters are embedded into a software based on HEVC with additional QTBT (Quadtree plus Binary Tree) and MTT (Multi-Type-Tree) block structure. In this setting, several measures to reduce the coding complexity of the tool are introduced, discussed and tested thoroughly. The coding complexity is reduced by up to 70% while maintaining over 80% of the gain. Overall, the diffusion filter method achieves average bitrate savings of 2.27% for Random Access having an average encoder runtime complexity of 119% and 117% decoder runtime complexity. For individual test sequences, results of 7.36% for Random Access are accomplished. 相似文献
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This study proposes an analytical and flexible terrain risk assessment method for military surveillance applications for mobile assets. Considering the risk as the degree of possibility of insurgent presence, the assessment method offers an efficient evaluation of risk in the surrounding terrain for military combat operating posts or observation posts. The method is designed for unmanned aerial vehicles as the surveillance assets of choice to improve the effectiveness of their use. Starting with the area map and geographical data, the target terrain is first digitized for space representation. Then the data of nine geographical parameters are used to formulate five contributing risk factors. These factors are incorporated in an analytical framework to generate a composite map with risk scores that reveal the potential high-risk spots in the terrain. The proposed method is also applied to a real-life case study of COP Kahler in Afghanistan, which was a target for insurgent attacks in 2008. The results confirm that when evaluated with the developed method, the region that the insurgents used to approach COP Kahler has high concentration of high-risk cells. 相似文献
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近年来深度学习迅猛发展,颠覆了语音识别、图像分类、文本理解等领域的算法设计思路。深度学习因其具备强大的特征提取能力,在图像识别领域的成绩尤为突出。然而深度学习与视频监控领域的结合并不多,由于深度模型具有多层网络结构,算法复杂度大,训练和更新模型时比较耗时,很难满足实时性要求。回顾了深度学习的发展史,介绍了最近10年来国内外深度学习主要模型,论述了基于深度学习的目标跟踪算法,指出了各算法的优缺点,最后对当前该领域存在的问题和发展前景进行了总结和展望。 相似文献
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人像智能分析指的是对视频或录像中的人像进行结构化和可视化分析,对目标人物进行性别、年龄、发型等特征的智能识别,这项技术在视频侦查中有极高的应用价值。人像识别早期的算法是通过人工提取特征,通过学习低级视觉特征来针对不同属性进行分类学习,这种基于传统方法的模型表现常常不尽如人意。在计算机视觉领域,通过海量图像数据学习的神经网络比传统方法有更丰富的信息量和特征可以被提取。文章尝试通过深度学习技术训练神经网络模型对行人进行检测和识别,对于衣着不同的行人进行智能识别,具有更好的鲁棒性,提升了视频人像识别的准确率,拓展了人工智能技术在身份识别领域的应用。 相似文献
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Frank H. P. Fitzek Martin Reisslein 《International Journal of Communication Systems》2004,17(5):421-435
Video streaming is expected to account for a large portion of the traffic in future networks, including wireless networks. It is widely accepted that the user datagram protocol (UDP) is the preferred transport protocol for video streaming and that the transmission control protocol (TCP) is unsuitable for streaming. The widespread use of UDP, however, has a number of drawbacks, such as unfairness and possible congestion collapse, which are avoided by TCP. In this paper we investigate the use of TCP as the transport layer protocol for streaming video in a multi‐code CDMA cellular wireless system. Our approach is to stabilize the TCP throughput over the wireless links by employing a recently developed simultaneous MAC packet transmission (SMPT) approach at the link layer. We study the capacity, i.e. the number of customers per cell, and the quality of service for streaming video in the uplink direction. Our extensive simulations indicate that streaming over TCP in conjunction with SMPT gives good performance for video encoded in a closed loop, i.e. with rate control. We have also found that TCP is unsuitable (even in conjunction with SMPT) for streaming the more variable open‐loop encoded video. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
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