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In this paper, we propose block diagonal movement technique to classify shots on video frame sequence. Both RGB color pixel values and Hue value are employed in the proposed technique. Since Key frames are essential to analysis on large amount of video sequence databases this paper uses surveillance video files to extract some meaningful information key frames from long video sequences. This purpose...
Nowadays, deep learning is very popular in a variety of research field due to its outperformance over the existing machine learning methods and its high generality over raw inputs. According to recent surveys, deep learning can give high performance in visual object recognition system. Human Action Recognition (HAR) is a promising research area over the computer vision research field due to its enormous...
The Internet of Things in which things or objects are connected becomes important in modern society. It also reflects to our Consumer World in which objects or things such as cell phones, consumer products, smart homes, cars, TVs etc. are in the World Wide connections. One of the most challenging problems is concerned with the defining and computing of reliability and availability measures since an...
This paper proposes a general intelligent video surveillance monitoring system to explore and examine some problems in animal behavior analysis particularly in cow behaviors. In this concern, farmers, animal health professionals and researchers have well recognized that analysis of changes in the behavioral patterns of cattle is an important factor for an animal health and welfare management system...
In this paper, a novel method for ranking consumer product brands by using link structures among the consumers is presented. The proposed ranking system will be established according to importance, popularity, reliability and relevancy based on consumer communication network. Using a modified version of the PageRank algorithm, the proposed ranking system is enforced by assigning each of them an authoritative...
In today consumer world, product search engines have been played key roles for consumer information seeking and decision making process. However, due to the volume, variety and velocity of information plus the nature of human beings, it becomes very hard to identify what information and how it is used by a consumer. Therefore, in this paper a Human Behavior Analyzer Framework is proposed to gain some...
New advances in embedded computing technology have opened up the potential for new era of consumer surveillance systems. This paper will explore and propose a new embedded modeling technique for the configuration of consumer video surveillance systems that can identify events of interest, especially on abandoned and stolen objects in indoor and outdoor environments. The proposed embedded system will...
A multi-typed information network is an information network which contains multiple types of objects having actions and interactions between each other. Although many studies on single typed information network haven been found in the literature, only a little has been known concerning with multi-typed information networks. On the other hand, multiple type information networks are ubiquitous and forming...
Background subtraction is one of important fundamental steps in many image processing applications such as object recognition, detection, tracking, human behavior analysis in video surveillance systems, etc. So the background subtraction method must be efficiency, that is saving time and space and have a good performance. In order to achieve this aim, a new background subtraction method is proposed...
More than ever before, the amount of data about consumers, suppliers and products has been exploding in today consumer world referred as “Big Data”. In addition, more data is available to the consumer world from multiple sources including social network platforms. In order to deal with such amount of data, a new emerging technology “Big Data Analytics” is explored and employed for analyzing consumer...
Today world has witnessed the catastrophic consequences of natural and man-made disasters are demanding the urgent need for more research to advance fundamental knowledge and innovation for disaster prevention, mitigation and management. At the same time, the world is in the age of the Big Data revolution which holds the potential to mitigate the effects of disaster events by enabling access to critical...
Popularity and reliability information are crucial ingredients of today social networking systems such as Facebook, Linked In, YouTube, Twitter, and so on. In this paper, we propose a stochastic model for measuring and ranking popularity and reliability information in social networks. Specifically, by using the relationships between co-occurring users, we model a Markov chain for reliability measures...
Popularity and reliability information are crucial ingredients of today social networking systems such as Facebook, Linked In, YouTube, Twitter, and so on. In this paper, we propose a stochastic model for measuring and ranking popularity and reliability information in social networks. Specifically, by using the relationships between co-occurring users, we model a Markov chain for reliability measures...
Consumers video surveillance systems are now being used not only for security reasons but also for better understanding consumer behaviors. In this paper, we propose a new visual behavior analysis tool for consumer video surveillance systems. This tool can be embedded in consumer videos to automatically detect and analyze unusual events. The proposed tool is developed by using a special type of Gamma...
In the consumer world, the ever growing image repositories in online shopping, consumer products images, consumer photos and video collections have resulted great demand of a system which can accurately retrieve similar images from image database. For this purpose, we propose a new concept of vision key for retrieving consumer product images. In our system, rather than considering an image as a whole,...
In this paper, we propose a new approach to analyze human behaviors by using a series of stochastic models composed of a Bivariate Gamma Markov model, a two dimensional correlated Random Walk model and a finite state Markov Chain model. Specifically, the proposed method contains three modules namely: (i) image analysis module, (ii) probability analysis module and (iii) event analysis module. We model...
Consumer video camera surveillance with the continuous advancements of image processing technologies is emerging for consumer world of applications. Technology for detecting objects left unattended in consumer world such as shopping malls, airports, railways stations has resulted in successful commercialization, worldwide sales and the winning of international awards. However, as a consumer video...
In this paper, we propose a stochastic web dynamic model based on the concept of queuing theory to measure popularity of websites in the World Wide Web. We assume that the characteristics of a website such as novelty, popularity, reliability, and relevancy are governed by two major forces: internal or self-growth of each website and external functions acting on the website. In stochastic language,...
Today video surveillance systems are widely used in public spaces, such as train stations or airports, to enhance security. In order to observe large and complex facilities a huge amount of cameras is required. These create a massive amount of data to be analyzed. It is therefore crucial to support human security staff with automatic surveillance applications, which will create an alert if security...
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