Object-based coding for long-term archive of surveillance video

Vetro, Anthony; Haga, Toshio; Sumi, Kosuke; Sun, Han

doi:10.1109/icme.2003.1221642

Cited by 52 publications

(32 citation statements)

References 2 publications

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“…Here we describe a surveillance application system that utilizes object-based coding techniques to achieve efficient storage of video content [49]. In this system, certain inaccuracies in the reconstructed scene can be tolerated; however, subjective quality and semantics of the scene must be strictly main tained.…”

Section: Surveillancementioning

confidence: 99%

Two-Dimensional Shape Coding

Ostermann¹,

Vetro²

2006

Signal Processing and Communications

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content-based storage and retrieval have to allow access to video data based on object descriptions, where objects are described by texture, shape, and motion. Studio and television postproduction applications require editing of video content with objects represented by texture and shape. For collaborative scene visualization like augmented reality, we need to place video objects into the scene. Mobile multimedia applications require content-based interactivity and content-based scalability in order to allocate limited bit rate or limited terminal resources to fit the individual needs. Security applications benefit from content-based scalability as well. All these applications share one common requirement: video content has to be easily accessible on an object basis. MPEG-4 Visual enables this functionality. The main part of this chapter describes MPEG-4 shape coding, the content-based interactivity enabling tool.Given the application requirements, video objects have to be described not only by texture, but also by shape. The importance of shape for video objects has been realized early on by the broadcasting and movie industries employing the so-called chroma-keying technique, which uses a predefined color in the video signal to define the background. Coding algorithms like objectbased analysis-synthesis coding (OBASC) [30| use shape as a parameter in addition to texture and motion for describing moving video objects. Second-generation image coding segments an image into regions and describes each region by texture and shape [28]. The purpose of using shape was to achieve better subjective picture quality, increased coding efficiency as well as an object-based video representation. Two types of VOs are distinguished. For opaque objects, binary shape information is transmitted. Transparent objects are described by gray-scale a-maps defining the outline as well as the transparency variation of an object. MPEG-4 Visual is the first international standard allowing the transmission of arbitrarily shaped video objects (VO) [21 J. Each frame of a VO is called video object plane (VOP

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Section: Surveillancementioning

confidence: 99%

Two-Dimensional Shape Coding

Ostermann¹,

Vetro²

2006

Signal Processing and Communications

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“…In such a manner the knowledge of segmented people and objects guides the adaptive compression. In [22], a similar approach for traffic surveillance is proposed, where objects are segmented and compressed differently in MPEG-4 standard for an offline annotated video server. Further, in [1] not only an object transcoding is discussed, but also the semantics is exploited at level of both objects and events.…”

Section: Related Workmentioning

confidence: 99%

Computer vision techniques for PDA accessibility of in-house video surveillance

Cucchiara

Grana

Prati

et al. 2003

First ACM SIGMM International Workshop on Video Surveillance - IWVS '03

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In this paper we propose an approach to indoor environment surveillance and, in particular, to people behaviour control in home automation context. The reference application is a silent and automatic control of the behaviour of people living alone in the house and specially conceived for people with limited autonomy (e.g., elders or disabled people). The aim is to detect dangerous events (such as a person falling down) and to react to these events by establishing a remote connection with low-performance clients, such as PDA (Personal Digital Assistant). To this aim, we propose an integrated server architecture, typically connected in intranet with network cameras, able to segment and track objects of interest; in the case of objects classified as people, the system must also evaluate the people posture and infer possible dangerous situations. Finally, the system is equipped with a specifically designed transcoding server to adapt the video content to PDA requirements (display area and bandwidth) and to the user's requests. The main issues of the proposal are a reliable real-time object detector and tracking module, a simple but effective posture classifier improved by a supervised learning phase, and an high performance transcoding inspired on MPEG-4 object-level standard, tailored to PDA. Results on different video sequences and performance analysis are discussed.

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“…Finally, most of the systems for security and safety purposes require remote access for external people (such as relatives or public officers for law enforcement). Thus, techniques of on-the-fly semantic video adaptation have been designed in order to allow to the user a remote access to visual data in an efficient and multimodal way [1,8]. This paper will describe the approach developed at ImageLab (http://imagelab.ing.unimo.it) in the project "Domotics for Disability" of home surveillance for elders and disabled people.…”

Section: Introductionmentioning

confidence: 99%

Using computer vision techniques for dangerous situation detection in domotic applications

Cucchiara

Grana

Prati

et al. 2004

Intelligent Distributed Surveillance Systems (IDSS-04)

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In this paper, we describe an integrated solution devised for In-House Video Surveillance, to control the safety of people living in a domestic environment. The system is composed of a robust moving object detection module, able to disregard shadows, a tracking module designed for large occlusion solution and of a posture detector. Shadows, large occlusions and deformable model of people are key features of in-house surveillance. Moreover, the requirements of high speed reaction to dangerous situations and the need to implement a reliable and low cost tele-viewing system, led to the introduction of a new multimedia model of semantic transcoding, capable to support different user's requests and constraints of their devices (PDA, smart phones,…). Our application context is the emerging area of Domotics (from the Latin word domus that means "home" and informatics) and, in particular, indoor video surveillance of the house where people with some difficulties (elders and disabled people) can now live in a sufficient degree of autonomy, thanks to the strong interaction with the new technologies that can be distributed in the house with affordable costs and high reliability.

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Object-based coding for long-term archive of surveillance video

Cited by 52 publications

References 2 publications

Two-Dimensional Shape Coding

Two-Dimensional Shape Coding

Computer vision techniques for PDA accessibility of in-house video surveillance

Using computer vision techniques for dangerous situation detection in domotic applications

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