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Camera tamper detection is the ability to detect faults and operational failures in video surveillance cameras by analyzing the video. Researchers have increasingly focused on such techniques attributing to the ubiquitous deployment of large scale surveillance systems. In this paper, a signal detection theory approach is proposed to quantitatively analyze the information being captured by the camera...
Faster R-CNN has established itself as the de-facto best object detector but it remains strongly limited in two aspects: (i) it is sensitive to background clutter and its classification performance decreases when it is confronted with more noisy proposals; (ii) it suffers when the objects vary largely in scale and specifically for the small objects. We address both issues with our geometric-proposals...
In this paper we would describe a vehicle detection technique that can be used for traffic surveillance systems. An intelligent traffic surveillance system, equipped with electronic devices, works by communicating with moving vehicles about traffic conditions, monitor rules and regulations and avoid collision between cars. Therefore the first step in this process is the detection of cars. The system...
The vibration response of a damaged bridge is known to have changed characteristics. To analyze the response, we start by collecting waveforms of the vibration immediately following the passage of a vehicle. We then need to isolate just those vibrations caused by a single heavy vehicle, if the vibration characteristics are to be accurate. In this paper, we propose a traffic-vibration analysis system...
Surveillance of public spaces is often conducted with the help of cameras placed at elevated positions. Recently, drones with high resolution cameras have made it possible to perform overhead surveillance of critical spaces. However, images obtained in these conditions may not contain enough body features to allow conventional biometric recognition. This paper introduces a novel gait recognition system...
This paper describes a distributed multi-user video analytics platform supporting multiple video providers and multiple analytics. Scalability, portability, adaptability and resiliency are the objectives of a well-integrated video analytics platform. Being an integrated system of systems comprised of various resource nodes, the challenges in building such an infrastructure ranges from efficient system...
Wireless Multimedia Sensor Networks (WMSN) are one of the emerging paradigms of the Internet of Things (IoT) that are used to retrieve content including scalar data, video and audio streams and still images from the physical environment. In contrast to scalar sensor (such as temperature and humidity sensor) nodes, multimedia sensor nodes capture high volumes of data and perform far more complex tasks...
In the traffic surveillance system (TSS), there are many factors affect the qualities of the result. Through practical application, it is difficult to determine which scene changing during the day period, from the daylight to nighttime, the conversion of the sunny and overcast, wet and dry scene. However, there have been no controlled studies which illustrate the method to distinguish environment...
In recent years, video surveillance technology has become ubiquitous in every sphere of our life. But automated video surveillance generates huge quantities of data, which ultimately does rely upon manual inspection at some stage. The present work aims to address this ever increasing gap between the volumes of actual data generated and the volume that can be reasonably inspected manually. It is laborious...
Low visibility is more likely to cause accidents, in order to fulfill the requirement of whole-distance surveillance as well as make full use of the resources surveillance cameras along the highway, a visibility detection Method based on the video camera calibration was proposed in this paper. At first, match the image block by the absolute difference of mismatch and SAD algorithm. After that, extract...
Surveillance systems play a critical role in security and surveillance. A surveillance system with cameras that work in the visible spectrum is sufficient for most cases. However, problems may arise during the night, or in areas with less than ideal illumination conditions. Cameras with thermal infrared technology can be a better option in these situations since they do not rely on illumination to...
Despite significant progress in the development of human action detection datasets and algorithms, no current dataset is representative of real-world aerial view scenarios. We present Okutama-Action, a new video dataset for aerial view concurrent human action detection. It consists of 43 minute-long fully-annotated sequences with 12 action classes. Okutama-Action features many challenges missing in...
Person re-identification is an important technique towards automatic search of a person's presence in a surveillance video. Two fundamental problems are critical for person re-identification:feature representation and metric learning. At present, there are many methods in the study of person re-identification, which has achieved remarkable results. Due to the difference of the data distribution in...
Traffic surveillance has always been a challenging task to automate. The main difficulties arise from the high variation of the vehicles appertaining to the same category, low resolution, changes in illumination and occlusions. Due to the lack of large labeled datasets, deep learning techniques still have not shown their full potential. In this paper, we train an Ensemble of Deep Networks (EDeN) to...
Onboard monocular cameras have been widely deployed in both public transit and personal vehicles. Obtaining vehicle-pedestrian near-miss event data from onboard monocular vision systems may be cost-effective compared with onboard multiple-sensor systems or traffic surveillance videos. But extracting near-misses from onboard monocular vision is challenging and little work has been published. This paper...
We describe a system for autonomous depth perception for surveillance in real world environments. With the ever-increasing need for surveillance, human operators are facing a challenging task to track suspicious behavior while looking at a large number of videos in real-time. We present an autonomous suspicious object detection method using depth information obtained from the Microsoft Kinect sensor...
This paper indicates the dataset and challenges evaluated under PETS2017. In this edition PETS continues the evaluation theme of on-board surveillance systems for protection of mobile critical assets as set in PETS 2016. The datasets include (1) the ARENA Dataset; an RGB camera dataset, as used for PETS2014 to PETS 2016, which addresses protection of trucks; and (2) the IPATCH Dataset; a multi sensor...
In the past decade, research in person re-identification (re-id) has exploded due to its broad use in security and surveillance applications. Issues such as inter-camera viewpoint, illumination and pose variations make it an extremely difficult problem. Consequently, many algorithms have been proposed to tackle these issues. To validate the efficacy of re-id algorithms, numerous benchmarking datasets...
Global motion estimation (GME) algorithms are typically employed on aerial videos captured by on-board UAV cameras to compensate for the artificial motion induced in these video frames due to camera motion. However, existing methods for GME have high computational complexity and are therefore not suitable for on-board processing in UAVs with limited computing capabilities. In this paper, we propose...
In this paper, we have proposed a method to detect abnormal events for human group activities. Our main contribution is to develop a strategy that learns with very few videos by isolating the action and by using supervised learning. First, we subtract the background of each frame by modeling each pixel as a mixture of Gaussians(MoG) to concatenate the higher order learning only on the foreground....
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