Online adaptive object tracking has been studied for years. These methods focus on dealing with the significant variation of object's appearance. However, over updating of the tracker may result in drifting proble...
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State-of-the-art objective image quality metrics are summarized and analyzed from a new perspective. Performance comparisons of existing metrics are firstly conducted on simulated turbulence-degraded images. Then expl...
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Graph-based representation of images is becoming a popular tool since it represents in a compact way the structure of a scene to be analyzed and allows for an easy manipulation of sub-parts or of relationships between...
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ISBN:
(数字)9783709164877
ISBN:
(纸本)9783211831212
Graph-based representation of images is becoming a popular tool since it represents in a compact way the structure of a scene to be analyzed and allows for an easy manipulation of sub-parts or of relationships between parts. Therefore, it is widely used to control the different levels from segmentation to interpretation.
The 14 papers in this volume are grouped in the following subject areas: hypergraphs, recognition and detection, matching, segmentation, implementation problems, representation.
Existing approaches for automatic image annotation usually suffer from two issues: (1) lacking a good quality distance metric for image semantic similarity measure; (2) rarely considering the correlation between label...
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Existing approaches for automatic image annotation usually suffer from two issues: (1) lacking a good quality distance metric for image semantic similarity measure; (2) rarely considering the correlation between labels assigned to each image. In this paper, we aim to resolve both of the problems simultaneously in a novel unified framework. Specifically, a proper distance metric is learned based on the structural SVM in a discriminative manner, which can optimize the ranking of the images induced by distances from a test image. Subsequently, a collaborative label propagation algorithm is leveraged to model the correlation between class labels in an explicit manner. Also, the learned metric is embedded in the propagation model. The integration of the two components leads to more accurate annotation results. The experiments conducted on the Corel dataset demonstrate the effectiveness of the proposed unified framework.
Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Tr...
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With the unprecedented growing of city economy and the crying need for public transportation,the ease of traffic related problems such as traffic jams has been a hard nut to crack everywhere. In this paper,a new metho...
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ISBN:
(纸本)9781424463473
With the unprecedented growing of city economy and the crying need for public transportation,the ease of traffic related problems such as traffic jams has been a hard nut to crack everywhere. In this paper,a new method based on convexity and concavity to better position the roads and streets of urban areas in order for further GPS/GIS integrated system,which is used for traffic flow analysis,traffic forecast,traffic induction and car positioning and tracking etc,is proposed. Compared with our previous work,this method can yield better results,and the accuracy that we get can be comparable to Google map. Our experiments are based on the data of the city of Shanghai and the results are very satisfying.
In recent years, iris recognition is becoming a very active topic in both research and practical applications. However, fake iris is a potential threat there are potential threats for iris-based systems. This paper pr...
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Diabetic retinopathy (DR) has already been one of the leading causes of vision loss. A large number of researches about deep learning-based DR screening using color retinal photography images have been proposed in rec...
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In this paper, we present a novel method to upsample the depth map obtained by the Time-of-Flight (ToF) camera with the guidance of the companion high resolution color image. The problem is modeled with an optimizatio...
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ISBN:
(纸本)9781479983407
In this paper, we present a novel method to upsample the depth map obtained by the Time-of-Flight (ToF) camera with the guidance of the companion high resolution color image. The problem is modeled with an optimization framework where we use a novel exponential function as the error norm. By using this novel error norm, our model could take the properties of the depth map itself into account. Depth discontinuity cues are obtained not only from the color image but also the depth map itself. To further enhance the performance, we perform a data driven selection of the parameter in the model to better fit the property of the depth map. Experimental results show that our method has excellent performance in smoothing the noise, preserving sharp depth discontinuities and suppressing the texture copy effect.
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