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This paper describes a novel system for automating data collection and surveying in a retail store using mobile robots. The manpower cost for surveying and monitoring the shelves in retail stores are high, because of which these activities are not repeated frequently causing reduced customer satisfaction and loss of revenue. Further, the accuracy of data collected may be improved by avoiding human...
In recent years, a number of fixed long-term underwater observatories (FUO) have been deployed to monitor marine habitats over time. HD cameras deployed on FUOs enable vision based studies of long-term processes in the monitored habitats. However, in many marine environments there is often only little a-priori knowledge about potential changes that can be expected or where such changes are likely...
Data centers are extremely important facilities that contain core business information and applications, but the energy consumption is an inevitable issue, so the thermal distribution monitoring is critical for data centers reliable and stable operation. Thermal information enables monitoring and autonomic thermal management in large data centers. Recent approaches that employed a mobile robot or...
Despite the huge research on crowd on behavior understanding in visual surveillance community, lack of publicly available realistic datasets for evaluating crowd behavioral interaction led not to have a fair common test bed for researchers to compare the strength of their methods in the real scenarios. This work presents a novel crowd dataset contains around 45,000 video clips which annotated by one...
In this paper we propose an automatic marine life monitoring system. First task in the monitoring process is to detect underwater moving objects as fishes. Second Task is to identify the species of the detected fish. Third task is to track the detected fish to avoid multiple counting and record their activities. Detection is performed using GMM based background subtraction method, classification is...
In this paper, we propose a novel approach to detect a targeted attack by visualizing the paths of lateral movement in which the attacker compromises several hosts in the targeted network step by step to achieve his final goal. To this end, we first identify a pair of hosts that has a relationship in which a host can have compromised the other host based on the suspiciousness of their activities and...
Coral reefs exhibit the highest biodiversity in the ocean and are an extremely vulnerable ecosystem. Monitoring the state of the reefs is a tedious process performed by human divers which can be automated. This paper presents the use of several inexpensive drifting sensor nodes in order to reconstruct a visual mosaic of a shallow coral reef. The drifters produce geo-referenced visual data from a downward...
Drowsy driving is considered one of the most serious causes of fatal traffic accidents, especially for long distance drivers who struggle significantly during monotonous driving conditions. As a result, various types of warning systems have been proposed among other preventive measure against drowsy driving. These systems issue a warning upon detecting a decline in driving performance as indicated...
This document presents a study regarding the potential of head movement in lie detection. The potential was analyzed using a non-invasive technique that detects the head movement out of video. In the literature there is a lot of information regarding lie indicators and for this reason we made a short review of them. Application was built in order to detect the head movement and head position by performing...
Brain-machine interfaces (BMIs) have demonstrated how they can be used for reaching tasks with both invasive and non-invasive signal recording methods. Despite the constant improvements in this field, there still exist diverse factors to overcome before achieving a natural control. In particular, the high variability of the brain signals often leads to the incorrect decoding of the subject intentions,...
This paper presents a novel approach for bird species identification that relies on both visual features extracted from unconstrained bird images and acoustic features extracted from bird vocalizations. The Scale Invariant Feature Transform (SIFT) detects local features in bird images, which are then used to train a support vector machine classifier. The instances that are not classified with a certain...
This paper presents a real-time monitoring of television advertisements using Bow. Frames are the basis of videos, thus an adaptive approach for extracting keyframes is proposed to describe video ads. Since in the BoW framework, the information of local feature points is lost during quantization, color name (CN) feature is introduced in this paper to enhance the discriminative power of visual words...
The school is a personnel intensive place, and it is easy to cause a fire. Through the video image processing method, the campus fire can be recognized effectively. Traditional campus fire recognition methods based on video image analysis don't analyze the color, texture and other low-level visual feature information of specific campus fire image. The cross validation performance is not good, and...
In the last decade, Global Navigation Satellite Systems (GNSS) have taken a key role in vehicular applications. However, GNSS-based systems are inoperable in enclosed areas like carparks. To overcome this problem, we developed an infrastructure-based positioning system which utilizes customary monocular surveillance cameras to determine the position of vehicles within a carpark. The position information...
This paper presents two fundamental contributions that can be very useful for any autonomous system that requires point correspondences for visual odometry. First, the Spatio-Temporal Monitor (STM) is an efficient method to identify good features to track by monitoring their spatiotemporal (x-y-t) appearance without any assumptions about motion or geometry. The STM may be used with any spatial (x-y)...
In recent years, driver drowsiness and distraction have been important factors in a large number of accidents because they reduce driver perception level and decision making capability, which negatively affect the ability to control the vehicle. One way to reduce these kinds of accidents would be through monitoring driver and driving behavior and alerting the driver when they are drowsy or in a distracted...
The world's oceans represent a vital resource to global economies and there exists huge economic opportunity that remains unexploited. However along with this huge potential there rests a responsibility into understanding the effects various developments may have on our natural ecosystem. This along with a variety of other issues necessitates a need for continuous and reliable monitoring of the marine...
People counting is a challenging task and has attracted much attention in the area of video surveillance. In this paper, we present an efficient self-learning people counting system which can count the exact number of people in a region of interest. This system based on bag-of-features model can effectively detect the pedestrians some of which are usually treated as background because they are static...
This paper deals with the realization of a visual monitoring system for the real time detection of spatters in laser beam welding (LBW). Spatters deteriorate the corrosion resistance and the aesthetics of the welding result. Therefore, the real time detection of spatters allows providing on-line quality information about the process, thus reducing material waste in production chains. The proposed...
This work is investigating the use of a multi-modal sensor network where visual sensors such as cameras and satellite imagers, along with context information can be used to complement and enhance the usefulness of a traditional in-situ sensor network in measuring and tracking some feature of a river or coastal location. This paper focuses on our work in relation to the use of an off the shelf camera...
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