The Experts below are selected from a list of 57 Experts worldwide ranked by ideXlab platform

Anthony C. Caputo - One of the best experts on this subject based on the ideXlab platform.

  • Introduction to Digital Video Security
    Digital Video Surveillance and Security, 2014
    Co-Authors: Anthony C. Caputo
    Abstract:

    This chapter describes the origins and theory behind Video surveillance and the same four key founding factors that are prevalent even today. General physical Security of lives, property, and equipment is still important and explains the evolution of visual surveillance, Digital Video surveillance, and how smarter systems help operators follow the four key factors. This chapter also presents case studies at various levels.

  • 1 – Introduction to Digital Video Security
    Digital Video Surveillance and Security, 2010
    Co-Authors: Anthony C. Caputo
    Abstract:

    Publisher Summary Visual surveillance began in the late nineteenth century to assist prison officials in the discovery of escape methods. The theory behind visual surveillance was founded on four key factors, namely, deterrence, efficiency, capable guardian, and detection. If potential criminals are aware of the possibility of being watched and recorded, they may determine that the risk of detection far outweighs the benefits. Visual surveillance as a deterrent is used from casinos to retail settings to public transportation. Reviewing Video surveillance footage at the same time as watching live surveillance provides additional information about a situation, allowing users to make better decisions about deploying the right kinds and numbers of resources. Digital Video Security (DVS) is also highlighted. DVS is intelligent networked Digital Video surveillance: the integration of all new and existing Security assets including cameras, alarms, networks, archiving, and analytics, with managed accessibility to monitor those assets from anywhere, at any time. It builds upon and extends current surveillance, Security, and IT infrastructure and investments. DVS is made possible by the interconnection and digitization of the world. The Digital Video formats and the delivery method ignore the traditional analog Video methodologies.

  • 1 introduction to Digital Video Security
    Digital Video Surveillance and Security, 2010
    Co-Authors: Anthony C. Caputo
    Abstract:

    Publisher Summary Visual surveillance began in the late nineteenth century to assist prison officials in the discovery of escape methods. The theory behind visual surveillance was founded on four key factors, namely, deterrence, efficiency, capable guardian, and detection. If potential criminals are aware of the possibility of being watched and recorded, they may determine that the risk of detection far outweighs the benefits. Visual surveillance as a deterrent is used from casinos to retail settings to public transportation. Reviewing Video surveillance footage at the same time as watching live surveillance provides additional information about a situation, allowing users to make better decisions about deploying the right kinds and numbers of resources. Digital Video Security (DVS) is also highlighted. DVS is intelligent networked Digital Video surveillance: the integration of all new and existing Security assets including cameras, alarms, networks, archiving, and analytics, with managed accessibility to monitor those assets from anywhere, at any time. It builds upon and extends current surveillance, Security, and IT infrastructure and investments. DVS is made possible by the interconnection and digitization of the world. The Digital Video formats and the delivery method ignore the traditional analog Video methodologies.

  • 4 – Understanding Networks and Networked Video
    Digital Video Surveillance and Security, 2010
    Co-Authors: Anthony C. Caputo
    Abstract:

    Publisher Summary This chapter provides an understanding of networks and networked Video. The system architecture that uses a server to provide resources to a group of individual computers (called clients, hosts, or nodes) is called a network or networking. The server is usually a high-performance computer that services many groups. Internet protocol (IP) network can change the way people use their computers and software by making it painless to work together as a team or group. It also provides the seamless interconnectivity that is the foundation of e-mail and the Internet, and has given way to Digital Video Security (DVS). Networks serve to bring together people with the best tools to accomplish the best work. Computer networks have given e-mail, file and print sharing, shared hardware resources, internet access, firewalls, web servers, and FTP servers.

  • 9 – Project Implementation
    Digital Video Surveillance and Security, 2010
    Co-Authors: Anthony C. Caputo
    Abstract:

    Publisher Summary This chapter focuses primarily on the management of a project and the specific deliverables required from previous Digital Video Security (DVS) projects. The complexity of any DVS system warrants a structured foundation, no matter the size. A project is defined as a temporary endeavor with a beginning and an end that creates a unique product, service, or result. A project is also considered progressive, documented, and managed. Larger projects can be divided into manageable phases or subprojects, which make it possible to assign these parts to other individuals, departments within the organization, or subcontractors who may have better expertise on the subject matter and thus greatly reduce the risk. Project management is the application of knowledge, skills, tools, and techniques to manage activities to meet project requirements. A project is accomplished through five stages, initiating, planning, executing, monitoring and controlling, and closing. In addition, this chapter also describes the project documentation deliverables; status reports are part of the project's document deliverables. Documentation is an essential part of any project and becomes even more important when the project is more complex.

Maguitman, Ana Gabriela - One of the best experts on this subject based on the ideXlab platform.

  • Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
    2019
    Co-Authors: Manera, José F., Vainstein Jonathan, Delrieux Claudio, Maguitman, Ana Gabriela
    Abstract:

    The aim of Action Recognition is the automated analysis and interpretation of events in Video sequences. As result of the applications that can be developed, and the widespread availability and popularization of Digital Video (Security cameras, monitoring, social networks, among many other), this area is currently the focus of a strong and wide research interest in various domains such as Video Security, humancomputer interaction, patient monitoring and Video retrieval, among others. Our long-term goal is to develop automatic action identification in Video sequences using Conditional Random Fields (CRFs). In this work we focus, as a case of study, in the identification of a limited set of tennis shots during tennis matches. Three challenges have been addressed: player tracking, player movements representation and action recognition. Video processing techniques are used to generate textual tags in specific frames, and then the CRFs are used as a classifier to recognise the actions performed in those frames. The preliminary results appear to be quite promising.Sociedad Argentina de Informática e Investigación Operativ

Baha Blanca - One of the best experts on this subject based on the ideXlab platform.

  • Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
    2013
    Co-Authors: F. Manera, Jonathan Vainstein, Claudio Delrieux, Ana Gabriela Maguitman, Baha Blanca
    Abstract:

    The aim of Action Recognition is the automated analysis and interpretation of events in Video sequences. As result of the ap- plications that can be developed, and the widespread availability and popularization of Digital Video (Security cameras, monitoring, social net- works, among many other), this area is currently the focus of a strong and wide research interest in various domains such as Video Security, human- computer interaction, patient monitoring and Video retrieval, among oth- ers. Our long-term goal is to develop automatic action identication in Video sequences using Conditional Random Fields (CRFs). In this work we focus, as a case of study, in the identication of a limited set of ten- nis shots during tennis matches. Three challenges have been addressed: player tracking, player movements representation and action recognition. Video processing techniques are used to generate textual tags in specic frames, and then the CRFs are used as a classier to recognise the ac- tions performed in those frames. The preliminary results appear to be quite promising.

Thomas Norman - One of the best experts on this subject based on the ideXlab platform.

  • 6 – Electronics Elements (Detailed Discussion)
    Integrated Security Systems Design, 2014
    Co-Authors: Thomas Norman
    Abstract:

    Chapter 6 includes a detailed discussion of design elements for alarm/access control systems, system servers, workstations, advanced elements, CCTV and Digital Video systems, wireless Digital Video, Security communications systems, command/control and communications (C3) consoles, console guard functions, and communications systems. Alarm/access control systems include identification devices such as ID badges, card readers, keypads, and biometric readers. Other devices include locks, door position switches, and request to exit devices. Chapter 6 covers virtually every type of electrified door and gate lock, as well as passage portals for vehicles for both administrative (daily use) and high-Security types. The different subsystems of an integrated Security system can be blended together into a single system. The system can also be interfaced with other systems to achieve advanced automated functions. Chapter 6 covers rudimentary, advanced, and sophisticated Video systems and also discusses how they can be integrated to other system elements to perform advanced alarm assessment functions. Both analog and Digital Video systems are discussed in detail, including imaging devices, lenses, lighting, transmission systems (analog and Digital, wired and wireless), and various analog and Digital methods of Video storage systems. Video analytics include fixed algorithm analytics, artificial intelligence learning algorithms, and facial recognition algorithms. Security communications are the root of response. Common technologies include two-way radios, cell phones, and intercoms. Intercoms can also be related to emergency phones and paging systems. Command and communications consoles are also discussed, including situational awareness software and physical Security information management systems (PSIMs).

Manera, José F. - One of the best experts on this subject based on the ideXlab platform.

  • Action Recognition in Tennis Videos using Optical Flow and Conditional Random Fields
    2019
    Co-Authors: Manera, José F., Vainstein Jonathan, Delrieux Claudio, Maguitman, Ana Gabriela
    Abstract:

    The aim of Action Recognition is the automated analysis and interpretation of events in Video sequences. As result of the applications that can be developed, and the widespread availability and popularization of Digital Video (Security cameras, monitoring, social networks, among many other), this area is currently the focus of a strong and wide research interest in various domains such as Video Security, humancomputer interaction, patient monitoring and Video retrieval, among others. Our long-term goal is to develop automatic action identification in Video sequences using Conditional Random Fields (CRFs). In this work we focus, as a case of study, in the identification of a limited set of tennis shots during tennis matches. Three challenges have been addressed: player tracking, player movements representation and action recognition. Video processing techniques are used to generate textual tags in specific frames, and then the CRFs are used as a classifier to recognise the actions performed in those frames. The preliminary results appear to be quite promising.Sociedad Argentina de Informática e Investigación Operativ