Query difficulty estimation (QDE) attempts to automatically predict the performance of the search results returned for a given query. QDE has been widely investigated in text document retrieval for many years. However...
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ISBN:
(纸本)9781479947607
Query difficulty estimation (QDE) attempts to automatically predict the performance of the search results returned for a given query. QDE has been widely investigated in text document retrieval for many years. However, few research works have been explored in image retrieval. State-of-the-art QDE methods in image retrieval mainly investigate the statistical characteristics (coherence, robustness, etc.) of the returned images to derive a value for indicating the query difficulty degree. To the best of our knowledge, little research has been done to directly estimate the real retrieval performance of the search results, such as average precision, instead of only an indicator. In this paper, we propose a novel query difficulty estimation approach which automatically estimate the average precision of the image search results. Specifically, we first select a set of query relevant and query irrelevant images for each query via pseudo relevance feedback. Then an efficient and effective voting scheme is proposed to estimate the relevance label of each image in the search results. Based on the images' relevance labels, the average precision of the search results returned for the given query is derived. The experimental results on a benchmark image search dataset demonstrate the effectiveness of the proposed method.
The High Efficiency Video Coding (HEVC) with the transform bypass mode is simple but inefficient for lossless coding. For this reason, we propose a novel transform to further eliminate the redundancy between residues ...
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ISBN:
(纸本)9781479934331
The High Efficiency Video Coding (HEVC) with the transform bypass mode is simple but inefficient for lossless coding. For this reason, we propose a novel transform to further eliminate the redundancy between residues of different blocks in intra prediction. Dependent on intra prediction modes, the proposed transform is adaptable to exploit correlations of residues formed by different modes. In order to accurately obtain parameters of the transform matrix, an approach similar to the Wiener filtering method is adopted. Experimental results show that on top of the lossless coding mode in HEVC, our method offers the performance with a 7.4% bit-rate reduction on average for All Intra Main configuration. Compared with other representative algorithms, our proposal still shows an improvement in the compression ratio, without substantial increases of computational complexity in the encoder or decoder.
In this paper, we try to deal with the problem of shadow detection from static images and video sequences. In instead to considering individual regions separately, we use relative illumination conditions between segme...
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Automatic annotation of images is of crucial importance in image retrieval and management systems. Most of the existing annotation methods rely on content-based approach to annotation, whose effectiveness is restricte...
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Automatic annotation of images is of crucial importance in image retrieval and management systems. Most of the existing annotation methods rely on content-based approach to annotation, whose effectiveness is restricted due to the semantic gap between low-level features and semantic annotations, as well as the irrelevance between annotations and image content. Recently, social media analysis has been investigated for image annotation. Inspired by the abundant social diffusion records of images in online social networks, we propose a novel image annotation approach based on social diffusion analysis. We present a common-interest model to interpret social diffusion, i.e. different images have different social diffusion routes due to the preferences of users, and such preferences are represented as common interests of pairwise users rather than personalized interests. We propose an image annotation framework that consists of learning of common interests, feature extraction from social diffusion records, and automatic annotation by learning to rank. Experimental results on a real-world dataset show that our proposed approach outperforms content-based and user-preference-based annotation methods.
Image compression had been extensively studied for reducing coding rate yet producing acceptable visual quality. However, there are many application scenarios where the compressed images are used for automatic recogni...
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ISBN:
(纸本)9781479973408
Image compression had been extensively studied for reducing coding rate yet producing acceptable visual quality. However, there are many application scenarios where the compressed images are used for automatic recognition rather than human viewing, thus the visual quality is no longer critical for compression. SIFT features have demonstrated their utility in many recognition scenarios and SIFT-preserving compression is developed recently. In this paper, we firstly study the SIFT-preserving compression of license plate images for recognition accuracy rather than visual quality. According to extracted SIFT features, each image is divided into SIFT coding-units and non-SIFT coding-units. Each coding-unit is assigned with a different quality parameter when using JPEG for compression. We compare our proposed scheme with the standard JPEG that uses a unified quality parameter. Experimental results with manually tuned parameters show that on average 14% bit-rate can be saved by our scheme, without any loss of recognition accuracy.
This system present a feasibility of computer-aided diagnosis, planning and simulation for orthodontic treatment. In the Visualization Toolkit (VTK) and Microsoft Foundation Classes (MFC) integrated environment, a fle...
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This system present a feasibility of computer-aided diagnosis, planning and simulation for orthodontic treatment. In the Visualization Toolkit (VTK) and Microsoft Foundation Classes (MFC) integrated environment, a flexible, friendly and functional interface for orthodontic treatment was designed. The methods of how to integrate VTK and MFC in different system are described, and the three-dimensional model of the dentition is reconstructed by using marching-cubes (MC) algorithms. Finally, the three-dimensional model for rendering and interaction is also introduced.
The relative rate of electrostatic discharge (ESD)-related failures or upsets is derived for various types of data centers based on different flooring systems and personal footwear. As the estimation of the actual num...
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In this paper, we study the existence, uniqueness and stability of periodic solution for a wide class of memristor-based neural networks with time-varying delays. By employing the topological degree theory in set-valu...
In this paper, we study the existence, uniqueness and stability of periodic solution for a wide class of memristor-based neural networks with time-varying delays. By employing the topological degree theory in set-valued analysis, differential inclusions theory and a new Lyapunov function method, we prove that the neural network has a unique periodic solution, which is globally exponentially stable. Moreover, we prove the existence, uniqueness and global exponential stability of equilibrium point for time-varying delayed memristor-based neural networks with constant coefficients. The obtained results improve and extend previous works on memristor-based or usual neural network dynamical systems with continuous or discontinuous right-hand side. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results.
This paper revisits the problem of estimating the domain of attraction for systems with saturation *** divide the input space into several regions. In one of these regions, none of the inputs saturate. In each of the ...
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ISBN:
(纸本)9781479947249
This paper revisits the problem of estimating the domain of attraction for systems with saturation *** divide the input space into several regions. In one of these regions, none of the inputs saturate. In each of the remaining regions, there is a unique input that saturates everywhere with the time-derivative of its saturated signal being zero. These special properties of the inputs in different regions of the input space are combined with an existing piecewise quadratic Lyapunov functions that contains the information of input saturation to arrive at a set of less conservative stability conditions, from which a larger level set of the piecewise quadratic Lyapunov function can be obtained as an estimate of the domain of *** results indicate that the proposed approach has the ability to obtain a significantly larger estimate of the domain of attraction than the existing methods.
Multiple scattering may render synthetic aperture radar (SAR) image interpretation difficult, particularly when it comes to imaging of man-made structures, which can be modeled as composite scatterers. To isolate diff...
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Multiple scattering may render synthetic aperture radar (SAR) image interpretation difficult, particularly when it comes to imaging of man-made structures, which can be modeled as composite scatterers. To isolate different scattering mechanism, we designed an airborne SAR experiment based on the high resolution, sub-metric to decimetric range, capabilities full-polarimetric SAR system, CARSS (Chinese Airborne Remote Sensing system), developing by IECAS. The imaging results are quite accord with the theoretical analysis. With polarimetric target decomposition, we can simply distinguish the different scattering mechanism. The idea to interpret the man-made targets as the combination of simple scattering mechanisms is supported by the experiment results.
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