—Inspired by the recent advances of image super-resolution using convolutional neural network (CNN), we propose a CNN-based block up-sampling scheme for intra frame coding. A block can be down-sampled before being co...
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Users’ download history is a primary data source for analyzing user interests. Recent work has shown that user interests are indeed time varying, and accurate profiling of user interest drifts requires the temporal d...
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Convolutional neural networks (CNNs) have achieved stateof-the-art results on many visual recognition tasks. However, current CNN models still exhibit a poor ability to be invariant to spatial transformations of image...
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With the explosive growth in the number of mobile terminals, the demand for visual communication with mobility is increasing. However, traditional solutions for mobility over IP network cannot always meet the demand o...
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ISBN:
(纸本)9781509053179
With the explosive growth in the number of mobile terminals, the demand for visual communication with mobility is increasing. However, traditional solutions for mobility over IP network cannot always meet the demand of satisfying visual communication. Named Data Networking (NDN) is a new communication model that aims to replace IP model brings a different background to mobile visual communication problems. In this paper, we take advantage of the NDN model to realize seamless mobile visual communication. We introduce a delegate with calculation functions and a globally unique identifier (GUID) which can provide native identity indication into the NDN mechanism. The use of GUID benefits real-time applications like visual communication and further works with the delegate to decrease unnecessary routing update. We also specify the naming rule and design a FIB+ to support seamless mobile visual communication. To test the performance of our solutions, we build a proof-of-concept prototype and run experiments on it. The experiments demonstrate that our solution can provide real-time video communication with seamless mobility experience.
Recently high-level pose features (HLPF) have been shown to be efficient for action recognition in joint-annotated tasks. However, the relative positions between pairs of joints in actual situations and the spatio-tem...
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ISBN:
(纸本)9781509015535
Recently high-level pose features (HLPF) have been shown to be efficient for action recognition in joint-annotated tasks. However, the relative positions between pairs of joints in actual situations and the spatio-temporal information are not considered in constructing HLPF. To tackle their problems, we propose a set of novel high-level pose features (NHLPF). Specifically, considering that the distances between adjacent pairs of joints usually remain unchanged, we propose a horizontally relative position feature and a vertically relative position feature. In addition, a joint inner product feature is proposed to code the spatial information among each triplet of joints. To code temporal information, we calculate the trajectories of the above-mentioned three types of features as corresponding trajectory features. Furthermore, to combine the spatial and temporal information, we present a joint energy change feature, which is designed using observations of the magnitude and direction of the force between joints. We evaluate our NHLPF on a benchmark dataset. The results show that NHPLF are superior features for action recognition.
In this paper, we consider video communication over fading channel, where the perfect instantaneous channel state information (CSI) is available at both sender and receiver. Most of existing coding schemes are ineffic...
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ISBN:
(纸本)9781479953424
In this paper, we consider video communication over fading channel, where the perfect instantaneous channel state information (CSI) is available at both sender and receiver. Most of existing coding schemes are inefficient in this communication scenario. The reason is that for digital coding scheme, it has high coding efficiency but unavoidably leads to the cliff effect;while for analog scheme, it has graceful video quality variation with channel varying, but has low coding efficiency. Hence, to integrate the advantages of digital coding and analog coding, we propose a hybrid digital-analog (HDA) scheme. In our scheme, we have adopted adaptive power allocation and adaptive forward error coding (FEC) in digital part to accommodate instantaneous channel quality. The evaluation results show that the proposed HDA scheme outperforms ParCast (a state-of-the-art analog scheme) 0.3~2.2dB under the channel Signal-to-Noise Ratio (SNR) from 3dB to 20dB.
Part-based trackers have achieved promising performance in many tracking tasks. However, most part-based trackers use the same feature representation for all parts and simply combine them together to form an integral ...
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ISBN:
(纸本)9781509053179
Part-based trackers have achieved promising performance in many tracking tasks. However, most part-based trackers use the same feature representation for all parts and simply combine them together to form an integral representation for the tracking target. It may not guarantee that all parts of the tracking target can well distinguish the foreground from the background. Better performance is expected by exploring different feature representations on different parts of the tracking target. In this paper, following the framework of the classic Compressive Tracker (CT), we model each part of the target adaptively by using a multi-dimensional color representation. By using color name, we select the color feature presentation that best distinguishes the foreground from background. In order to better handle deformation and illumination change, we use multi-Gaussian to model different appearance changes of the tracking target. Both qualitative and quantitative evaluations demonstrate that the proposed method makes a consistent performance improvement compared with the conventional Compressive Tracker on tracking benchmark dataset. Besides, it also outperforms many state-of-the-art trackers while running at averagely 20 frames per second (FPS).
Scattering structure features of targets is of great importance for Synthetic Aperture Radar (SAR) image analysis. In this paper, a novel algorithm for aircraft recognition in high resolution apron area of SAR images ...
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ISBN:
(纸本)9781509033331
Scattering structure features of targets is of great importance for Synthetic Aperture Radar (SAR) image analysis. In this paper, a novel algorithm for aircraft recognition in high resolution apron area of SAR images is proposed. The algorithm combines the strength of gradient saliency map and scattering structure features to improve accuracy and efficiency. Specially, Constant False-Alarm Rate (CFAR) algorithm is carried out to segment images. Then, a new efficient object locating method based on directional local gradient map is proposed to detect aircraft targets. Then, the candidate slices as well as template slices are modeled using Gaussian Mixture Model (GMM), which will be treated as structure features. In the recognition stage, a novel similarity measurement algorithm based on Kullback-Leibler Divergence for GMM models is proposed for classification. We conduct experiments on the dataset with 3.0m resolution and the recognition results demonstrate the accuracy of our proposed method.
Ionosphere is an important factor in highresolution spaceborne synthetic aperture radar（SAR） and geosynchronous（GEO） SAR. An approach based on point target deviation between range sub-images is proposed in this pa...
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Ionosphere is an important factor in highresolution spaceborne synthetic aperture radar（SAR） and geosynchronous（GEO） SAR. An approach based on point target deviation between range sub-images is proposed in this paper to estimate and correct the ionosphere. Due to the dispersion effect, the ionosphere causes propagation delay deviation in range subimages with different carrier frequency. This deviation can be used to estimate the total electron content（TEC） along the propagation path, and then the ionospheric effects can be corrected according to the signal model deduced out in this paper. The simulation results show that our approach is valid and robust.
InSAR interferogram quality assessment is a key step for the using of interferogram map. Traditionally, the interferogram is qualitatively assessed visually and quantitatively assessed by the number of residues. Howev...
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InSAR interferogram quality assessment is a key step for the using of interferogram map. Traditionally, the interferogram is qualitatively assessed visually and quantitatively assessed by the number of residues. However, the important structure information is hardly quantifiable. This paper presents a novel index to evaluate the quality of InSAR interferogram based on connected area. After discomposing the fringes into independent connected areas, we analyze the statistical ratio of an area to its margin. Then we use the ratio as an index to quantitatively evaluate the interferogram. In the end, the presented index is used for the filtered interferogram of popular filters, and the results fit the visual judging.
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