Robust Adaptive Intra Refresh for Multiview Video

Transmission error propagation in wireless multimedia communication systems has become a recurring problem. This persistent problem has led to grave consequences on the visual quality of the decoded video. It is against this backdrop that, we present an adaptive intra refresh (AIR) error-resilient coding tool to mitigate the effect of transmission error propagation in 3D video communications. This work utilizes periodic insertion of intra macroblocks in badly error-infected frames temporally as well as related frames in the multi view video scheme. Our objective is to maximize the transmission efficiency while ensuring the transmission robustness of the coded bitstream. The selection of periodic macroblocks is based on areas with high motion above a pre-set threshold. The coding modes of the macroblocks are based on the distortion expectation due to transmission errors. Extensive simulation results show significant improvement in both objective and subjective video quality at different intra refresh rates

Applying psychological science to the CCTV review process: a review of cognitive and ergonomic literature

As CCTV cameras are used more and more often to increase security in communities, police are spending a larger proportion of their resources, including time, in processing CCTV images when investigating crimes that have occurred (Levesley & Martin, 2005; Nichols, 2001). As with all tasks, there are ways to approach this task that will facilitate performance and other approaches that will degrade performance, either by increasing errors or by unnecessarily prolonging the process. A clearer understanding of psychological factors influencing the effectiveness of footage review will facilitate future training in best practice with respect to the review of CCTV footage. The goal of this report is to provide such understanding by reviewing research on footage review, research on related tasks that require similar skills, and experimental laboratory research about the cognitive skills underpinning the task. The report is organised to address five challenges to effectiveness of CCTV review: the effects of the degraded nature of CCTV footage, distractions and interrupts, the length of the task, inappropriate mindset, and variability in people’s abilities and experience. Recommendations for optimising CCTV footage review include (1) doing a cognitive task analysis to increase understanding of the ways in which performance might be limited, (2) exploiting technology advances to maximise the perceptual quality of the footage (3) training people to improve the flexibility of their mindset as they perceive and interpret the images seen, (4) monitoring performance either on an ongoing basis, by using psychophysiological measures of alertness, or periodically, by testing screeners’ ability to find evidence in footage developed for such testing, and (5) evaluating the relevance of possible selection tests to screen effective from ineffective screener

Towards transparent telepresence

It is proposed that the concept of transparent telepresence can be closely approached through high fidelity technological mediation. It is argued that the matching of the system capabilities to those of the human user will yield a strong sense of immersion and presence at a remote site. Some applications of such a system are noted. The concept is explained and critical system elements are described together with an overview of some of the necessary system specifications

A Survey on Multimedia-Based Cross-Layer Optimization in Visual Sensor Networks

Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available bandwidth, end-to-end delay and packet error rates. In such context, multimedia coding is required for data compression and error-resilience, also ensuring energy preservation over the path(s) toward the sink and improving the end-to-end perceptual quality of the received media. Cross-layer optimization may enhance the expected efficiency of VSNs applications, disrupting the conventional information flow of the protocol layers. When the inner characteristics of the multimedia coding techniques are exploited by cross-layer protocols and architectures, higher efficiency may be obtained in visual sensor networks. This paper surveys recent research on multimedia-based cross-layer optimization, presenting the proposed strategies and mechanisms for transmission rate adjustment, congestion control, multipath selection, energy preservation and error recovery. We note that many multimedia-based cross-layer optimization solutions have been proposed in recent years, each one bringing a wealth of contributions to visual sensor networks

Decisional Fit under Turbulent Circumstances

The purpose of this communication is to study the effect of a recent networking decision support system (called Link 16) on decision performance, within the specific context of military operations. Based on a new decision model - the Decisional Fit Model ? we demonstrate that Link 16 fits with task characteristics and decision maker internal representations of the problem domain. However, improvements could be considered in order to increase the level of fit.Systèmes d'aide à la décision, Modèle d'adéquation, prise de décision en situation, conscience de la situation, performance décisionnelle

Delivery of Personalized and Adaptive Content to Mobile Devices:A Framework and Enabling Technology

Many innovative wireless applications that aim to provide mobile information access are emerging. Since people have different information needs and preferences, one of the challenges for mobile information systems is to take advantage of the convenience of handheld devices and provide personalized information to the right person in a preferred format. However, the unique features of wireless networks and mobile devices pose challenges to personalized mobile content delivery. This paper proposes a generic framework for delivering personalized and adaptive content to mobile users. It introduces a variety of enabling technologies and highlights important issues in this area. The framework can be applied to many applications such as mobile commerce and context-aware mobile services

Ensemble-Empirical-Mode-Decomposition based micro-Doppler signal separation and classification

The target echo signals obtained by Synthetic Aperture Radar (SAR) and Ground Moving Target Indicator (GMTI platforms are mainly composed of two parts, the micro-Doppler signal and the target body part signal. The wheeled vehicle and the track vehicle are classified according to the different character of their micro-Doppler signal. In order to overcome the mode mixing problem in Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) is employed to decompose the original signal into a number of Intrinsic Mode Functions (IMF). The correlation analysis is then carried out to select IMFs which have a relatively high correlation with the micro-Doppler signal. Thereafter, four discriminative features are extracted and Support Vector Machine (SVM) classifier is applied for classification. The experimental results show that the features extracted after EEMD decomposition are effective, with up 90% success rate for classification using one feature. In addition, these four features are complementary in different target velocity and azimuth angles

Ensemble-Empirical-Mode-Decomposition based micro-Doppler signal separation and classification

The target echo signals obtained by Synthetic Aperture Radar (SAR) and Ground Moving Target Indicator (GMTI platforms are mainly composed of two parts, the micro-Doppler signal and the target body part signal. The wheeled vehicle and the track vehicle are classified according to the different character of their micro-Doppler signal. In order to overcome the mode mixing problem in Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) is employed to decompose the original signal into a number of Intrinsic Mode Functions (IMF). The correlation analysis is then carried out to select IMFs which have a relatively high correlation with the micro-Doppler signal. Thereafter, four discriminative features are extracted and Support Vector Machine (SVM) classifier is applied for classification. The experimental results show that the features extracted after EEMD decomposition are effective, with up 90% success rate for classification using one feature. In addition, these four features are complementary in different target velocity and azimuth angles

’Looking Through a Soda Straw’: Mediated Vision in Remote Warfare

Image-guided military operations embed soldiers into a complex system of image production, transmission, and perception. These soldiers separate their bodies from the battlefield, but they also mediate between them. In particular, remote controlled operations of so-called unmanned aerial systems (UAS) require the synchronization between human actors and technical sensors in real-time, such as the knowledge of a situation. This situational awareness relies almost exclusively on the visualization of sensory data. This human-machine entanglement corresponds to a new operative modality of images which differs from previous forms of real-time imaging such as live broadcasting, as it is based on a feedback-loop that turns the observer into an actor. Images are not simply analyzed and interpreted but become agents in a socio- technological assemblage. The paper will draw upon this functional shift of images from a medium of visualization towards a medium that guides operative processes. Based on the analysis of vision, architecture, and navigation in remote warfare, it will discuss how real-time video technology and the mobilization of sensor and transmission technology produce a type of intervention, in which action and perception is increasingly organized and determined by machines.