Visual surveillance in dynamic scenes, especially for humans and vehicles, is currently one of the most active research topics in computer vision. It has a wide spectrum of promising applications, including access control in special areas, human identification at a distance, crowd flux statistics and congestion analysis, detection of anomalous behaviors, and interactive surveillance using multiple cameras, etc. In general, the processing framework of visual surveillance in dynamic scenes includes the following stages: modeling of environments, detection of motion, classification of moving objects, tracking, understanding and description of behaviors, human identification, and fusion of data from multiple cameras. We review recent developments and general strategies of all these stages. Finally, we analyze possible research directions, e.g., occlusion handling, a combination of twoand three-dimensional tracking, a combination of motion analysis and biometrics, anomaly detection and behavior prediction, content-based retrieval of surveillance videos, behavior understanding and natural language description, fusion of information from multiple sensors, and remote surveillance.

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A survey on visual surveillance of object motion and behaviors

This tutorial paper reviews the theory and design of codes for hiding or embedding information in signals such as images, video, audio, graphics,and text. Such codes have also been called watermarking codes; they can be used in a variety of applications, including copyright protection for digital media, content authentication, media forensics, data binding, and covert communications. Some of these applications imply the presence of an adversary attempting to disrupt the transmission of information to the receiver; other applications involve a noisy, generally unknown, communication channel. Our focus is on the mathematical models, fundamental principles, and code design techniques that are applicable to data hiding. The approach draws from basic concepts in information theory, coding theory, game theory, and signal processing,and is illustrated with applications to the problem of hiding data in images.

Data-Hiding Codes

Information technology advances have brought forth new challenges in healthcare information management, due to the vast amount of medical data that needs to be efficiently stored, retrieved, and distributed, and the increased security threats that explicitly have to be addressed. The paper discusses the perspectives of digital watermarking in a range of medical data management and distribution issues, and proposes a complementary and/or alternative tool that simultaneously addresses medical data protection, archiving, and retrieval, as well as source and data authentication. The scheme imperceptibly embeds in medical images multiple watermarks conveying patient's personal and examination data, keywords for information retrieval, the physician's digital signature for authentication, and a reference message for data integrity control. Experimental results indicate the efficiency and transparency of the scheme, which conforms to the strict requirements that apply to regions of diagnostic significance

Multiple Image Watermarking Applied to Health Information Management

Motion detection is the first essential process in the extraction of information regarding moving objects and makes use of stabilization in functional areas, such as tracking, classification, recognition, and so on. In this paper, we propose a novel and accurate approach to motion detection for the automatic video surveillance system. Our method achieves complete detection of moving objects by involving three significant proposed modules: a background modeling (BM) module, an alarm trigger (AT) module, and an object extraction (OE) module. For our proposed BM module, a unique two-phase background matching procedure is performed using rapid matching followed by accurate matching in order to produce optimum background pixels for the background model. Next, our proposed AT module eliminates the unnecessary examination of the entire background region, allowing the subsequent OE module to only process blocks containing moving objects. Finally, the OE module forms the binary object detection mask in order to achieve highly complete detection of moving objects. The detection results produced by our proposed (PRO) method were both qualitatively and quantitatively analyzed through visual inspection and for accuracy, along with comparisons to the results produced by other state-of-the-art methods. The analyses show that our PRO method has a substantially higher degree of efficacy, outperforming other methods by an metric accuracy rate of up to 53.43%.

An Advanced Motion Detection Algorithm With Video Quality Analysis for Video Surveillance Systems

Visual sensor networks (VSNs) are receiving a lot of attention in research, and at the same time, commercial applications are starting to emerge. VSN devices come with image sensors, adequate processing power, and memory. They use wireless communication interfaces to collaborate and jointly solve tasks such as tracking persons within the network. VSNs are expected to replace not only many traditional, closed-circuit surveillance systems but also to enable emerging applications in scenarios such as elderly care, home monitoring, or entertainment. In all of these applications, VSNs monitor a potentially large group of people and record sensitive image data that might contain identities of persons, their behavior, interaction patterns, or personal preferences. These intimate details can be easily abused, for example, to derive personal profiles. The highly sensitive nature of images makes security and privacy in VSNs even more important than in most other sensor and data networks. However, the direct use of security techniques developed for related domains might be misleading due to the different requirements and design challenges. This is especially true for aspects such as data confidentiality and privacy protection against insiders, generating awareness among monitored people, and giving trustworthy feedback about recorded personal data—all of these aspects go beyond what is typically required in other applications. In this survey, we present an overview of the characteristics of VSN applications, the involved security threats and attack scenarios, and the major security challenges. A central contribution of this survey is our classification of VSN security aspects into data-centric, node-centric, network-centric, and user-centric security. We identify and discuss the individual security requirements and present a profound overview of related work for each class. We then discuss privacy protection techniques and identify recent trends in VSN security and privacy. A discussion of open research issues concludes this survey.

Security and Privacy Protection in Visual Sensor Networks: A Survey

In automatic video surveillance (VS) systems, the issue of authenticating the video content is of primary importance. Given the ease with which digital images and videos can be manipulated, practically they do not have any value as legal proof, if the possibility of authenticating their content is not provided. In this paper, the problem of authenticating video surveillance image sequences is considered. After an introduction motivating the need for a watermarking-based authentication of VS sequences, a brief survey of the main watermarking-based authentication techniques is presented and the requirements that an authentication algorithm should satisfy for VS applications, are discussed. A novel algorithm which is suitable for VS visual data authentication is also presented and the results obtained by applying it to test data are discussed.

F. Bartolini

Papers

Image authentication techniques for surveillance applications