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Unusual behaviour detection and information extraction in streams of short documents and files (emails, news, tweets, log files, messages, etc.) are important problems in security applications. In [1], [2], a new approach to rapid change detection and automatic summarization of large documents was introduced. This approach is based on a theory of social networks and ideas from image processing and...
The objective of human re-identification is to recognize a specific individual on different locations and to determine whether an individual has already appeared. This is especially in multi-camera networks with non-overlapping fields of view of interest. However, this is still an unsolved computer vision task due to several challenges, e.g. significant changes of appearance of humans as well as different...
This paper presents a method for extractive multi-document summarization that explores a two-phase clustering approach that, combined with a sentence simplification procedure, aims to generate more useful summaries. First, sentences are clustered by similarity, and one sentence per cluster is selected, to reduce redundancy. Then, in order to group them according to topics, those sentences are clustered...
Obfuscation methods were proposed for protecting programs from cracking. These methods convert program into incomprehensible one, such as change symbol names from meaningful to meaningless. As a result, secret information in the program can be hidden. However, obfuscation methods are not evaluated sufficiently. This paper evaluates incomprehensibility of the obfuscated programs using queue based virtual...
The human factors involved in an unmanned aerial system (UAS) come in a variety of forms that has largely gone poorly represented in literature. In this paper, a holistic approach is taken to identify not only the individual aspects but the interconnection of the human-UAS interaction. First, an examination of human factors involved in a UAS are presented. Next, the metrics of human performance, such...
Salient region-based image retrieval is one of the hotspots in the domain of content-based image retrieval; however the metrics about region saliency is not in the uniform frame. The research on visual attention has shown that the factors including color, texture, scale and position influence on visual perception mostly. Consequently, the algorithm of salient region extraction is proposed by using...
Automatic assessment of image quality in accordance with the human visual system (HVS) finds application in various image processing tasks. In the last decade, a substantial proliferation in image quality assessment (IQA) based on structural similarity has been observed. The structural information estimation includes statistical values (mean, variance, and correlation), gradient information, Harris...
It is essential for robots to be highly usable to achieve increased acceptance among target population. In this paper, we put forward a metric that measures easiness of acceptance using the length of time to initiate interaction, total interaction time, time needed to identify perception-reaction phenomenon, its occurrence, number of violations and affective interaction factor. This measure would...
We present an automated approach to music search and playlist generation based on fractal dimensions of music. We compute 372 power-law metrics per song capturing statistical proportions of musical material. Using attribute selection and principal component analysis, we have reduced these metrics to approximately 45 independent features. These have been shown to capture important aspects of music...
Among 2D-to-3D image conversion methods, those involving human operators have been most successful but also time-consuming and costly. Automatic methods, that typically make use of a deterministic 3D scene model, have not yet achieved the same level of quality as they often rely on assumptions that are easily violated in practice. In this paper, we adopt the radically different approach of “learning”...
The design of automated online security and intrusion tolerance solutions for computer systems and networks is a theoretically achievable objective. However, after two decades of research, this objective has still not yet successfully passed the practicality test to become widely adopted. We believe that the main reason behind this gap lies in the misleading definition of autonomous security that...
We propose an unsupervised image segmentation method based on texton similarity and mode seeking. The input image is first convolved with a filter-bank, followed by soft clustering on its filter response to generate textons. The input image is then superpixelized where each belonging pixel is regarded as a voter and a soft voting histogram is constructed for each superpixel by averaging its voters'...
This fast abstract outlines a novel mechanism for monitoring the security state of a system, using intelligent testing agents to instigate and then depress security activities.
We present a machine learning framework that automatically generates a model set of landmarks for some class of registered 3D objects: here we use human faces. The aim is to replace heuristically-designed landmark models by something that is learned from training data. The value of this automatically generated model is an expected improvement in robustness and precision of learning-based 3D landmarking...
This work intends to identify common performance metrics for task-oriented human-robot interaction. We present a methodology to assess the system performance of a human-robot team in achievement of collective tasks. We propose a systematic approach that addresses the performance of both the human user and the robotic agent as a team. Toward this end, we attempt to determine the true time that an operator...
Supervoxel segmentation has strong potential to be incorporated into early video analysis as superpixel segmentation has in image analysis. However, there are many plausible supervoxel methods and little understanding as to when and where each is most appropriate. Indeed, we are not aware of a single comparative study on supervoxel segmentation. To that end, we study five supervoxel algorithms in...
Progress in our understanding of brain functions relies on our capability to explore the human cortical surface at a fine scale (typically 1.5 mm isotropic at 3T). For this purpose, high accuracy is required for all processing steps from image acquisition to data analysis. For group studies, the high intersubject variability of the human cortices hampers their precise registration. Based on the hypothesis...
This paper is an attempt to explore a human element not easily solved in the image processing communities. The problem statement is vague but important to address. What is a good image? More specifically, if a low contrast image is presented, at what level of enhancement is good enough for a human observer? This of course depends on diverse elements, e.g., personal preference, emotional state, physical...
This paper presents the result of a recent large-scale subjective study of image retargeting quality on a collection of images generated by several representative image retargeting methods. Owning to many approaches to image retargeting that are developed, there is a need for a diverse independent public database of the retargeted images and the corresponding subjective scores that is freely available...
Human activity recognition using wearable body sensors is playing a significant role in ubiquitous and mobile computing. One of the issues related to this wearable technology is that the captured activity signals are highly dependent on the location where the sensors are worn on the human body. Existing research work either extracts location information from certain activity signals or takes advantage...
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