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The TRECVID report of 2010 [14] evaluated video shot boundary detectors as achieving "excellent performance on [hard] cuts and gradual transitions." Unfortunately, while re-evaluating the state of the art of the shot boundary detection, we found that they need to be improved because the characteristics of consumer-produced videos have changed significantly since the introduction of mobile...
Human re-identification remains one of the fundamental, difficult problems in video surveillance and analysis. Current metric learning algorithms mainly focus on finding an optimized vector space such that observations of the same person in this space have a smaller distance than observations of two different people. In this paper, we propose a novel metric learning approach to the human reidentification...
Vessel tortuosity is an important parameter in determining the presence or the severity of various diseases that are diagnosed based on the pathology of vessels. An accurate quantification of vessel tortuosity would therefore be of great clinical significance. Usually, the branches of blood vessels are also captured, along with the major blood vessel, in the medical images, thereby posing a challenge...
In this paper, we present a novel approach for recognition of human faces using Markov Random Fields (MRF) and Bayesian models. We examine the relationship between feature vectors in a close proximity system. The feature vectors are coefficients of the 2D Gabor Wavelet Transform (DWGT). The MRF is implemented to match the constraint configurations between the feature vectors. The MRFs posterior probability...
In this paper, we describe a novel method using only optical flow from a single camera and inertial information to quickly initialize, deploy, and autonomously stabilize an inherently unstable aerial vehicle. Our approach requires a minimal number of tracked features in only two consecutive frames and inertial readings eliminating the need of long feature tracks or local maps and rendering it inherently...
This paper tackles the problem of categorizing materials and textures by exploiting the second order statistics. To this end, we introduce the Extrinsic Vector of Locally Aggregated Descriptors (E-VLAD), a method to combine local and structured descriptors into a unified vector representation where each local descriptor is a Covariance Descriptor (CovD). In doing so, we make use of an accelerated...
It is a well-known fact that financial markets react to information. Even though this relationship seems simple, finding evidence is not easy since information is embedded in textual news releases. Only recent have researchers started to look at the content of news. Interestingly, previous work avoids the inference of a causal relationship between news messages and abnormal returns. In this paper,...
Trustworthiness is a very critical element and should be treated as an important reference when customers try to select proper e-commerce systems. Trustworthiness evaluation requires the management of a wide variety of information types, parameters and uncertainties. Multi-criteria decision analysis (MCDA) has been regarded as a suitable set of methods to perform trustworthiness evaluations as a result...
Virtual Network Embedding (VNE) is one of the critical techniques in network virtualization. In this paper, we attempt to improve the performance of VNE in terms of acceptance ratio of Virtual Network (VN) requests by considering resource fragmentation in a substrate network. Different from existing work, we involve a new metric called Resource Fragmentation Degree (RFD) to quantitatively measure...
A major challenge in topic classification (TC) is the high dimensionality of the feature space. Therefore, feature extraction (FE) plays a vital role in topic classification in particular and text mining in general. FE based on cosine similarity score is commonly used to reduce the dimensionality of datasets with tens or hundreds of thousands of features, which can be impossible to process further...
Billions of internet end-users and device to device connections contribute to the significant data growth in recent years, large scale, unstructured, heterogeneous data and the corresponding complexity present challenges to the conventional real-time online fraud detection system security. With the advent of big data era, it is expected the data analytic techniques to be much faster and more efficient...
In this work, we propose a research method to summarize popular information from massive tourism blog data. First, we crawl blog contents from website and segment each of them into a semantic word vector separately. Then, we select the geographical terms in each word vector into a corresponding geographical term vector and present a new method to explore the hot tourism locations and, especially,...
In this study, we have proposed a domain-independent unsupervised text segmentation method, which is applicable to even if unseen single document. This proposed method segments text documents by evaluating similarity between sentences. It is generally difficult to calculate semantic similarity between words that comprise sentences when the domain knowledge is insufficient. This problem influences...
For a large-scale software system, especially an online service system, when a performance issue occurs, it is desirable to check whether this issue has occurred before. If there are past similar issues, a known remedy could be applied. Otherwise, a new troubleshooting process may have to be initiated. The symptom of a performance issue can be characterized by a set of metrics. Due to the sophisticated...
Matched-texture coding (MTC) exploits the redundancy of textured regions in natural images in order to achieve low-encoding-rate structurally lossless compression. A key element of MTC identifying large image blocks that can be replaced with previously encoded blocks that have similar structure. The side matching (SM) approach attempts to do this by matching the upper and left boundary (side) of a...
In this work, a measure of similarity based on the matching of multivariate probability density functions (PDFs) is proposed. In consonance with the information theoretic learning (ITL) framework, the affinity comparison between the joint PDFs is performed using a quadratic distance, estimated with the aid of the Parzen window method with Gaussian kernels. The motivation underlying this proposal is...
Recent advances in distance function learning have demonstrated that learning a good distance metric can greatly improve the performance in a wide variety of tasks in data mining and web search. A major problem in such scenarios is the limited labeled knowledge available for learning the user intentions. Furthermore, distances are inherently local, where a single global distance function may not capture...
Cloud infrastructures are prone to various anomalies due to their ever-growing complexity and dynamics. Monitoring behavior of dynamic resource management systems is necessary to guarantee cloud reliability. In this paper, we present AMAD, a system designed for detecting an abusive use of dynamic virtual machine migration, in the case of the abusive virtual machine migration attack. This attack is...
Full-dimension multiple-input multiple-output (FD-MIMO) systems, in which base stations are equipped with a large number of antennas in a two-dimensional panel, has received considerable attention from academia researchers and industry practitioners. Compared with legacy cellular communication systems, FD-MIMO systems can achieve significantly higher spectral efficiency with high order multi-user...
Reforms in the educational system emphasize more on continuous assessment. The descriptive examination question paper when compared to objective question paper acts as a better aid in continuous assessment for testing the progress of a student under various cognitive levels at different stages of learning. Unfortunately, assessment of descriptive answers is found to be tedious and time consuming by...
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