The scalable and multiview extensions of the High Efficiency Video Coding share the same high-level syntax coding structure. For the scalable extension, the motion field of the inter-layer reference picture is modifie...
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ISBN:
(纸本)9781479983926
The scalable and multiview extensions of the High Efficiency Video Coding share the same high-level syntax coding structure. For the scalable extension, the motion field of the inter-layer reference picture is modified through Motion Field Mapping before used for motion vector prediction. However, the motion field of the inter-layer reference picture is used without modification in the multiview extension. In this paper, a disparity-compensated inter-layer motion prediction is proposed for multiview video coding to achieve disparity compensation in inter-layer motion prediction using the scaled reference layer offset. The experimental results show that comparing with the multiview extension anchor, the proposed method achieves an average of 1.1% bitrate reduction.
In order to adapt different scale land cover segmentation, an optimized approach under the guidance of k-means clustering for multi-scale segmentation is proposed. At first, small scale segmentation and k-means cluste...
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This paper introduces a novel global patch matching method that focuses on how to remove fronto-parallel bias and obtain continuous smooth surfaces with assuming that the scenes covered by stereos are piecewise contin...
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In passive radars, coherent integration is an essential method to achieve processing gain for target detection. The cross ambiguity function(CAF) and the method based on matched filtering are the most common approache...
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In passive radars, coherent integration is an essential method to achieve processing gain for target detection. The cross ambiguity function(CAF) and the method based on matched filtering are the most common approaches. The method based on matched filtering is an approximation to CAF and the procedure is:(1) divide the signal into snapshots;(2) perform matched filtering on each snapshot;(3) perform fast Fourier transform(FFT) across the snapshots. The matched filtering method is computationally affordable and can offer savings of an order of 1000 times in execution speed over that of CAF. However, matched filtering suffers from severe energy loss for high speed targets. In this paper we concentrate mainly on the matched filtering method and we use keystone transform to rectify range migration. Several factors affecting the performance of coherent integration are discussed based on the matched filtering method and keystone transform. Modified methods are introduced to improve the performance by analyzing the impacts of mismatching, precision of the keystone transform, and discretization. The modified discrete chirp Fourier transform(MDCFT) is adopted to rectify the Doppler expansion in a multi-target scenario. A novel velocity estimation method is proposed, and an extended processing scheme presented. Simulations show that the proposed algorithms improve the performance of matched filtering for high speed targets.
According to the actual situation of Pearl River basin and the existing evaluation index systems of river-lake health, a new evaluation index system of river-lake health in Pearl River basin was built. The river-lake ...
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ISBN:
(纸本)9781467376648
According to the actual situation of Pearl River basin and the existing evaluation index systems of river-lake health, a new evaluation index system of river-lake health in Pearl River basin was built. The river-lake health assessment system was built using ArcGIS as a development platform. The data was obtained based on remote sensing and GIS. The rapidness and visualization of river-lake health assessment were realized by this system, which could support the protection services in Pearl River basin.
With the exponential growth of surveillance videos, conference videos and sports videos, videos with static cameras present an unprecedented challenge for high-efficiency video coding technology. The existing schemes ...
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With the exponential growth of surveillance videos, conference videos and sports videos, videos with static cameras present an unprecedented challenge for high-efficiency video coding technology. The existing schemes developed for these videos mostly encode the background as the long-term reference (LTR) to further improve the coding efficiency. However, since the bit allocation of the long-term background reference is not intensively studied, the coding efficiency is still unsatisfactory. Based on the stability analysis of the video content, an efficient background picture coding algorithm for videos obtained from static cameras, which is embedded with the basic unit level bit allocation, is proposed in this paper. Experimental results reveal that on top of the default mode in HEVC, our method offers the performance with 10.8% BD-rate reduction on average. Compared with the state-of-the-art algorithm, it still outperforms for kinds of test sequences with negligible increases of computational complexity in both encoder and decoder.
A visually inspired variational method for automatic image registration is proposed to solve local deformation which traditional global registration model cannot well satisfy. The variational model considers local tra...
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This paper focuses on discovering bursty topics from news stream. Previous work usually apply Kleinberg's modeling of burst to topics estimated by a topic model such as Latent Dirichlet Allocation (LDA) and Dynami...
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This paper focuses on discovering bursty topics from news stream. Previous work usually apply Kleinberg's modeling of burst to topics estimated by a topic model such as Latent Dirichlet Allocation (LDA) and Dynamic Topic Model (DTM). However, Kleinberg's model is originally proposed for the burst of keywords, the frequency counts it models are not proper to describe the burst states of topics, leading to some unwanted results. A more reasonable way is to model the influence burst states put on each document's topic distribution. Considering this, we propose a unified statistical model that takes the burst states as markov latent variables that influence the topic allocation of documents. We derive a Gibbs sampling algorithm for the proposal. Experiment results confirm our model's advantages both qualitatively and quantitatively.
In this paper we propose the rating Correlated Topic Model for rating-based collaborative filtering, which improves the performance of the state-of-the-art Latent Semantic Models in two aspects: (1), making the predic...
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In this paper we propose the rating Correlated Topic Model for rating-based collaborative filtering, which improves the performance of the state-of-the-art Latent Semantic Models in two aspects: (1), making the prediction accuracy more robust to the topic number K;(2), improving the recommendation quality for users with few existed ratings. We achieve our goals by employing the Logistic Normal distribution to capture the correlation between latent topics following the Correlated Topic Model, as well as modifying the generative process to meet the requirement of rating-based collaborative filtering. We derive a parameter estimation algorithm based on variational inference for the proposal. Experiment results on the Movielens data set demonstrate our model's advantages on both referred aspects.
When browsing through photographs taken during a trip, it can be a distressing discovery to find many other bystanders captured within the frame. A visually compelling snapshot preserves the desired subject in the for...
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