Human violence recognition and detection in surveillance videos

  • On Surveillance for Safety Critical Events: In-Vehicle Video Networks for Predictive Driver Assistance Systems E. Ohn-Bar , A. Tawari, S. Martin, and M. Trivedi Computer Vision and Image Understanding ( CVIU ) , 2015 Impact factor: 2.77
Objects in the outdoor surveillance are often detected in far field. Most existing digital video-surveillance systems rely on human observers In this study, we focus on detecting humans and do not consider recognition of their complex activities. Human detection is a difficult task from a...

E.T.S is the abbreviation for Event Trigger System, which is a new notification system that brings faster and more precise detection with the help of human detectors or external alarm devices. It is self-evident that the false alarm rate of the system simply using motion detection is relatively high, compared with E.T.S, and it causes a waste ...

The Surveillance Resource Center provides members of the public health surveillance community organized, easy access to guidance developed by CDC and its partners for improving the practice of surveillance. Public health surveillance refers to the collection, analysis, and use of data to target public health prevention.
  • Computer Vision Group at Vietnam National University of HCMC - Univ of Natural Sciences Our research are concentrated on Object detection, recognition, tracking, Human activity recognition and tracking. Vincent Torre Lab at SISSA; Virage, Inc. Computer Vision Group at Virginia Tech Applied research in computer vision and pattern recognition.
  • Object detection and tracking are important and challenging tasks in many computer vision applications such as surveillance, vehicle navigation, and autonomous robot navigation.Video surveillance in a dynamic environment, especially for humans and vehicles, is one of the current challenging research topics in computer vision. It
  • Surveillance Face Recognition Dataset (QMUL-SurveFace), a large scale surveillance face recognition challenge of native low-resolution face images from surveillance videos, with 463,507 facial images of 15,573 identities ; iLIDS Video re-IDentification (iLIDS-VID) Dataset (ECCV 2014, PAMI 2016)

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    The lab has been active in a number of research topics including object detection and recognition, face identification, 3-D modeling from a sequence of images, activity recognition, video retrieval and integration of vision with natural language queries. More details can be found here.

    The VIRAT Video Dataset is designed to be realistic, natural and challenging for video surveillance domains in terms of its resolution, background clutter, diversity in scenes, and human activity/event categories than existing action recognition datasets. It has become a benchmark dataset for the computer vision community.

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    An approach to detect and track groups of people in video-surveillance applications, and to automatically recognize their behavior. 8. MODULES DESCRIPTION: Event Detection: Event recognition is a key task in automatic understanding of video sequences.  The typical detection...

    Oct 30, 2007 · The purpose of this article is to provide an SSE optimized, C++ library for face detection that I developed, so you can start using it right now in your video surveillance applications. The classifiers supplied with it were trained on my webcam images collected over a period of time with different lighting conditions and it detects me without a ...

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    May 11, 2019 · Driven by artificial intelligence, facial recognition allows officers to submit images of people’s faces, taken in the field or lifted from photos or video, and instantaneously compare them to ...

    Recognition of Human Actions in Low Resolution Videos . Recognition of human actions from a distant view is a challenging problem in computer vision. The available visual cues are particularly sparse and vague under this scenario. We proposed an action descriptor, which is composed of time series of subspace projected histogram-based features.

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    Computer Vision Group at Vietnam National University of HCMC - Univ of Natural Sciences Our research are concentrated on Object detection, recognition, tracking, Human activity recognition and tracking. Vincent Torre Lab at SISSA; Virage, Inc. Computer Vision Group at Virginia Tech Applied research in computer vision and pattern recognition.

    Surveillance Face Recognition Dataset (QMUL-SurveFace), a large scale surveillance face recognition challenge of native low-resolution face images from surveillance videos, with 463,507 facial images of 15,573 identities ; iLIDS Video re-IDentification (iLIDS-VID) Dataset (ECCV 2014, PAMI 2016)

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    Detection DIY Detection, Pro Detection ... State and Local governments can now save both time and money when purchasing surveillance equipment from surveillance-video ...

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    May 07, 2015 · The Bosphorus Database is intended for those researching 3D and 2D human face processing tasks. These include expression recognition, facial action unit detection, facial action unit intensity estimation, face recognition under adverse conditions, deformable face modeling, and 3D face reconstruction.

    Apr 24, 2019 · In this Oct. 31, 2018, photo, Watrix employees demonstrate their firm's gait recognition software at their company's offices in Beijing. A Chinese technology startup hopes to begin selling ...

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    City centre surveillance: Many large cities have nighttime crime and antisocial behaviour problems, such as drunkenness, fights, vandalism, breaking and entering shop windows, etc. Often these cities have video cameras already installed, but what is lacking is a semi-automatic analysis of the video stream.

    ... However, detection and tracking of human from images or videos is a challenging problem facing by researchers due to variations in pose, clothing In contrast, violence recognition such as events related to fight and knife, has gained less attention. The capability of visual surveillance can be used...

Video surveillance can be used to detect the presence of humans, their behavior, and Automatic human detection and tracking is an important feature of video surveillance systems. Human detection systems can have different goals such as detecting the presence of humans, recognition...
Aug 26, 2016 · Our goal is to determine if a violence occurs in a video (recognition) and when it happens (detection). Firstly, we propose an extension of the Improved Fisher Vectors (IFV) for videos, which allows to represent a video using both local features and their spatio-temporal positions.
As you will see from the tutorials explored in this article, some of the most popular applications in computer vision deals with the detection, tracking and the recognition of objects and humans. Whether you are looking to build a robot able to detect a human or an automated system able to detect an object, the Raspberry Pi board is the center ...
The Image Processing and Pattern Recognition Research Center is part of the Computer Science Department from the Technical University of Cluj-Napoca. Our main activities are research and teaching in the fields of image processing, pattern recognition, computer vision, hardware design for image acquisition and processing.