Physics-Based Technique for Protecting Privacy in Surveillance Videos

This paper describes a physics-based technique for protecting the privacy of people in videos as defined by the MediaEval 2013 Visual Privacy task. We propose a physics-based approach which estimates the full spectrum of the surface spectral reflectance from the video. Whereby the wavelength which corresponds to the global minimum of the spectral curve (an intrinsic feature of the material) at a pixel is calculated and converted to RGB values which are used to filter pixels that belong to a moving object. This effectively implements visual privacy protection by replacing foreground pixel colour by another which is related to intrinsic optical properties of the original pixel. Both objective and subjective evaluations are performed using both video analytics algorithm and user studies in order to evaluate the proposed technique

Prediction architecture based on block matching statistics for mixed spatial-resolution multi-view video coding

The use of mixed spatial resolutions in multi-view video coding is a promising approach for coding videos efficiently at low bitrates. It can achieve a perceived quality, which is close to the view with the highest quality, according to the suppression theory of binocular vision. The aim of the work reported in this paper is to develop a new multi-view video coding technique suitable for low bitrate applications in terms of coding efficiency, computational and memory complexity, when coding videos, which contain either a single or multiple scenes. The paper proposes a new prediction architecture that addresses deficiencies of prediction architectures for multi-view video coding based on H.264/AVC. The prediction architectures which are used in mixed spatial-resolution multi-view video coding (MSR-MVC) are afflicted with significant computational complexity and require significant memory size, with regards to coding time and to the minimum number of reference frames. The architecture proposed herein is based on a set of investigations, which explore the effect of different inter-view prediction directions on the coding efficiency of multi-view video coding, conduct a comparative study of different decimation and interpolation methods, in addition to analyzing block matching statistics. The proposed prediction architecture has been integrated with an adaptive reference frame ordering algorithm, to provide an efficient coding solution for multi-view videos with hard scene changes. The paper includes a comparative performance assessment of the proposed architecture against an extended architecture based on the 3D digital multimedia broadcast (3D-DMB) and the Hierarchical B-Picture (HBP) architecture, which are two most widely used architectures for MSR-MVC. The assessment experiments show that the proposed architecture needs less bitrate by on average 13.1 Kbps, less coding time by 14% and less memory consumption by 31.6%, compared to a corresponding codec, which deploys the extended 3D-DMB architecture when coding single-scene videos. Furthermore, the codec, which deploys the proposed architecture, accelerates coding by on average 57% and requires 52% less memory, compared to a corresponding codec, which uses the HBP architecture. On the other hand, multi-view video coding which uses the proposed architecture needs more bitrate by on average 24.9 Kbps compared to a corresponding codec that uses the HBP architecture. For coding a multi-view video which has hard scene changes, the proposed architecture yields less bitrate (by on average 28.7 to 35.4 Kbps), and accelerates coding time (by on average 64 and 33%), compared to the HBP and extended 3D-DMB architectures, respectively. The proposed architecture will thus be most beneficial in low bitrate applications, which require multi-view video coding for video content depicting hard scene changes

Predicting household water use behaviour for improved hygiene practices in internet of things environment via dynamic behaviour intervention model

Recent advances in Internet of Things (IoT) enabled technologies allow the intelligent sensor systems to effectively and efficiently observe and identify human behaviour in many applications, particularly in energy consumption and healthcare sectors. One typical case is that how to use IoT technologies to understand human water use behaviour for improved and sustained hygiene practice. Traditionally, static behaviour intervention models are widely utilised to simulate behaviour intervention process over time. These static methods can predict targeted human behaviour reasonably well, but lack of capabilities on understanding and responding behaviour change process in IoT environments. In this study, the authors proposed a dynamic behaviour intervention model for predicting household water user behaviour for improved hygiene practices. This model is based on an expanded theory of planned behaviour (ETPB), and adopted structure equation model approach and control engineering concept. A case study of household water consumption model using artificial neural network is utilised to evaluate intervention trend of proposed ETPB dynamic behaviour model with system parameter identification. The ETPB dynamic model has been proved to be effective for modelling human behaviour intervention process

OPNET-Based Performance Analysis of a Multi-agent Architecture for Managing the Mobile Content Delivery Process

This paper addresses the problem of mobile content delivery failure in wireless data networks, and the resulting wastage of communication resources. In these networks, many content delivery transactions fail due to inadequate device or channel capability, possibly after a partial delivery of the content requested by the user. The paper evaluates the performance of a solution devised to enhance and optimise the delivery of mobile content, as a new approach for reducing the probability of wasting valuable communication resources. The proposed solution is a layered multi-agent architecture which is offered in two alternative configurations: a centralised-decision configuration, and a distributed-decision configuration. Furthermore, a baseline configuration (with no agents for managing the content delivery process) is used in the paper, for the purpose of comparative performance evaluation. The simulation results have shown that on average, under heavy traffic conditions and for two levels of device capability (low or high performance device), the distributed-decision configuration outperforms the other two configurations, in terms of lower agent communication overhead, admitting more transactions and reducing bandwidth utilisation. Overall, compared to the baseline system, the layered multi-agent system performs more efficiently in heavy traffic networks and for poor device capability. However, as would be expected, the multi-agent system performs worse than the baseline system under conditions of high device capability, due to the overhead introduced by the communication between agents. The results support the intuitive expectations of agent behaviour in telecommunication systems

A local error bound approach to simplifying complex geometric models

This paper presents a new error bound simplification algorithm for complex geometric models. A lower polygon count approximation of the input model is generated by performing edge collapse operations. The collapse vertex is constrained to lie within a localised tolerance volume built around the edge collapse neighbourhood. This constraint ensures that all points on the simplified surface are within a user specified distance from the surface after the previous edge collapse

Spectral-360: A Physics-Based Technique for Change Detection

This paper presents and assesses a novel physics-based change detection technique, Spectral-360, which is based on the dichromatic color reflectance model. This approach, uses image formation models to computationally estimate, from the camera output, a consistent physics-based color descriptor of the spectral reflectance of surfaces visible in the image, and then to measure the similarity between the full-spectrum reflectance of the background and foreground pixels to segment the foreground from a static background. This method represents a new approach to change detection, using explicit hypotheses about the physics that create images. The assumptions which have been made are that diffuse-only-reflection is applicable, and the existence of a dominant illuminant. The objective evaluation performed using the 'changedetection.net 2014' dataset shows that our Spectral-360 method outperforms most state-of-the-art methods