Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

A Comprehensive Benchmarking Framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM

Process mining encompasses the research area which is concerned with knowledge discovery from information system event logs. Within the process mining research area, two prominent tasks can be discerned. First of all, process discovery deals with the automatic construction of a process model out of an event log. Secondly, conformance checking focuses on the assessment of the quality of a discovered or designed process model in respect to the actual behavior as captured in event logs. Hereto, multiple techniques and metrics have been developed and described in the literature. However, the process mining domain still lacks a comprehensive framework for assessing the goodness of a process model from a quantitative perspective. In this study, we describe the architecture of an extensible framework within ProM, allowing for the consistent, comparative and repeatable calculation of conformance metrics. For the development and assessment of both process discovery as well as conformance techniques, such a framework is considered greatly valuable.

How activation, entanglement, and searching a semantic network contribute to event memory

Free association norms indicate that words are organized into semantic/associative neighborhoods within a larger network of words and links that bind the net together. We present evidence indicating that memory for a recent word event can depend on implicitly and simultaneously activating related words in its neighborhood. Processing a word during encoding primes its network representation as a function of the density of the links in its neighborhood. Such priming increases recall and recognition and can have long lasting effects when the word is processed in working memory. Evidence for this phenomenon is reviewed in extralist cuing, primed free association, intralist cuing, and single-item recognition tasks. The findings also show that when a related word is presented to cue the recall of a studied word, the cue activates it in an array of related words that distract and reduce the probability of its selection. The activation of the semantic network produces priming benefits during encoding and search costs during retrieval. In extralist cuing recall is a negative function of cue-to-distracter strength and a positive function of neighborhood density, cue-to-target strength, and target-to cue strength. We show how four measures derived from the network can be combined and used to predict memory performance. These measures play different roles in different tasks indicating that the contribution of the semantic network varies with the context provided by the task. We evaluate spreading activation and quantum-like entanglement explanations for the priming effect produced by neighborhood density.

SAIVT-QUT@TRECVid 2012 : interactive surveillance event detection

In this paper, we propose an approach which attempts to solve the problem of surveillance event detection, assuming that we know the definition of the events. To facilitate the discussion, we first define two concepts. The event of interest refers to the event that the user requests the system to detect; and the background activities are any other events in the video corpus. This is an unsolved problem due to many factors as listed below: 1) Occlusions and clustering: The surveillance scenes which are of significant interest at locations such as airports, railway stations, shopping centers are often crowded, where occlusions and clustering of people are frequently encountered. This significantly affects the feature extraction step, and for instance, trajectories generated by object tracking algorithms are usually not robust under such a situation. 2) The requirement for real time detection: The system should process the video fast enough in both of the feature extraction and the detection step to facilitate real time operation. 3) Massive size of the training data set: Suppose there is an event that lasts for 1 minute in a video with a frame rate of 25fps, the number of frames for this events is 60X25 = 1500. If we want to have a training data set with many positive instances of the event, the video is likely to be very large in size (i.e. hundreds of thousands of frames or more). How to handle such a large data set is a problem frequently encountered in this application. 4) Difficulty in separating the event of interest from background activities: The events of interest often co-exist with a set of background activities. Temporal groundtruth typically very ambiguous, as it does not distinguish the event of interest from a wide range of co-existing background activities. However, it is not practical to annotate the locations of the events in large amounts of video data. This problem becomes more serious in the detection of multi-agent interactions, since the location of these events can often not be constrained to within a bounding box. 5) Challenges in determining the temporal boundaries of the events: An event can occur at any arbitrary time with an arbitrary duration. The temporal segmentation of events is difficult and ambiguous, and also affected by other factors such as occlusions.

Linking the fifth pillar to the first in the UN Decade of Action

The UN Decade of Action outlines five pillars of activity within a safe system framework to achieve the goal of slowing and then reversing the global growth in road traffic fatalities, especially in low-income and middle-income countries. The first four pillars - road safety management, safer roads and mobility, safer vehicles, and safer road users – have a strong focus on prevention of road traffic crashes and mitigation of energy exchange when a crash occurs. The fifth pillar – post-crash response – is far more specific, focusing only on crash victims in the event of a safe system failure. The victims appear to be relevant to the first four pillars only insofar as their numbers can be used to evaluate the success of road safety programs and identify the target groups and contributing factors. This paper argues that a better understanding of the lived experience of long term disability from traffic crashes has the potential to provide a feedback loop from the fifth pillar to the first. Research conducted in Thailand with male crash victims with spinal injury demonstrates that patterns of attribution and social and cultural factors have important implications for road safety management and for interventions aimed at influencing behaviour. In addition, the mobility constraints experienced by people with long term disability can point to systemic issues that might otherwise go unnoticed. The UN Decade of Action can benefit from a more thorough exploration of the experiences and circumstances of people with long term disability as the result of a road traffic crash. Rather than being evidence of the failure of the safe system, they can inform the development of more effective road safety management on low-income and middle-income countries.

Algorithm for queue estimation with loop detector of time occupancy in off-ramps on signalized motorways

Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.

Traffic queue estimation for metered motorway on-ramps through use of loop detector time occupancies

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

Visualising security incidents through event aggregation

Extracting and aggregating the relevant event records relating to an identified security incident from the multitude of heterogeneous logs in an enterprise network is a difficult challenge. Presenting the information in a meaningful way is an additional challenge. This paper looks at solutions to this problem by first identifying three main transforms; log collection, correlation, and visual transformation. Having identified that the CEE project will address the first transform, this paper focuses on the second, while the third is left for future work. To aggregate by correlating event records we demonstrate the use of two correlation methods, simple and composite. These make use of a defined mapping schema and confidence values to dynamically query the normalised dataset and to constrain result events to within a time window. Doing so improves the quality of results, required for the iterative re-querying process being undertaken. Final results of the process are output as nodes and edges suitable for presentation as a network graph.

Studies in power hardware in the loop (PHIL) simulation using real-time digital simulator (RTDS)

In power hardware in the loop (PHIL) simulations, a real-time simulated power system is interfaced to a piece of hardware, usually called hardware under test (HuT). A PHIL test can be realized using several simulation tools. Among them Real Time Digital Simulator (RTDS) is an ideal tool to perform complex power system simulations in near real-time. Stable operation of the entire system, along with the accuracy of simulation results are the main concerns regarding a PHIL simulation. In this paper, a simulated power network on RTDS will be interfaced to HuT through a voltage source converter (VSC). Issues around stability and other interface problems are studied and a new method to stabilize some unstable PHIL cases is proposed. PHIL simulation results in PSCAD and RSCAD are presented.

Profiling event logs to configure risk indicators for process delays

Risk identification is one of the most challenging stages in the risk management process. Conventional risk management approaches provide little guidance and companies often rely on the knowledge of experts for risk identification. In this paper we demonstrate how risk indicators can be used to predict process delays via a method for configuring so-called Process Risk Indicators(PRIs). The method learns suitable configurations from past process behaviour recorded in event logs. To validate the approach we have implemented it as a plug-in of the ProM process mining framework and have conducted experiments using various data sets from a major insurance company.

Inflow cannula design for biventricular assist devices

Cardiovascular diseases are a leading cause of death throughout the developed world. With the demand for donor hearts far exceeding the supply, a bridge-to-transplant or permanent solution is required. This is currently achieved with ventricular assist devices (VADs), which can be used to assist the left ventricle (LVAD), right ventricle (RVAD), or both ventricles simultaneously (BiVAD). Earlier generation VADs were large, volume-displacement devices designed for temporary support until a donor heart was found. The latest generation of VADs use rotary blood pump technology which improves device lifetime and the quality of life for end stage heart failure patients. VADs are connected to the heart and greater vessels of the patient through specially designed tubes called cannulae. The inflow cannulae, which supply blood to the VAD, are usually attached to the left atrium or ventricle for LVAD support, and the right atrium or ventricle for RVAD support. Few studies have characterized the haemodynamic difference between the two cannulation sites, particularly with respect to rotary RVAD support. Inflow cannulae are usually made of metal or a semi-rigid polymer to prevent collapse with negative pressures. However suction, and subsequent collapse, of the cannulated heart chamber can be a frequent occurrence, particularly with the relatively preload insensitive rotary blood pumps. Suction events may be associated with endocardial damage, pump flow stoppages and ventricular arrhythmias. While several VAD control strategies are under development, these usually rely on potentially inaccurate sensors or somewhat unreliable inferred data to estimate preload. Fixation of the inflow cannula is usually achieved through suturing the cannula, often via a felt sewing ring, to the cannulated chamber. This technique extends the time on cardiopulmonary bypass which is associated with several postoperative complications. The overall objective of this thesis was to improve the placement and design of rotary LVAD and RVAD inflow cannulae to achieve enhanced haemodynamic performance, reduced incidence of suction events, reduced levels of postoperative bleeding and a faster implantation procedure. Specific objectives were: * in-vitro evaluation of LVAD and RVAD inflow cannula placement, * design and in-vitro evaluation of a passive mechanism to reduce the potential for heart chamber suction, * design and in-vitro evaluation of a novel suture-less cannula fixation device. In order to complete in-vitro evaluation of VAD inflow cannulae, a mock circulation loop (MCL) was developed to accurately replicate the haemodynamics in the human systemic and pulmonary circulations. Validation of the MCL’s haemodynamic performance, including the form and magnitude of pressure, flow and volume traces was completed through comparisons of patient data and the literature. The MCL was capable of reproducing almost any healthy or pathological condition, and provided a useful tool to evaluate VAD cannulation and other cardiovascular devices. The MCL was used to evaluate inflow cannula placement for rotary VAD support. Left and right atrial and ventricular cannulation sites were evaluated under conditions of mild and severe heart failure. With a view to long term LVAD support in the severe left heart failure condition, left ventricular inflow cannulation was preferred due to improved LVAD efficiency and reduced potential for thrombus formation. In the mild left heart failure condition, left atrial cannulation was preferred to provide an improved platform for myocardial recovery. Similar trends were observed with RVAD support, however to a lesser degree due to a smaller difference in right atrial and ventricular pressures. A compliant inflow cannula to prevent suction events was then developed and evaluated in the MCL. As rotary LVAD or RVAD preload was reduced, suction events occurred in all instances with a rigid inflow cannula. Addition of the compliant segment eliminated suction events in all instances. This was due to passive restriction of the compliant segment as preload dropped, thus increasing the VAD circuit resistance and decreasing the VAD flow rate. Therefore, the compliant inflow cannula acted as a passive flow control / anti-suction system in LVAD and RVAD support. A novel suture-less inflow cannula fixation device was then developed to reduce implantation time and postoperative bleeding. The fixation device was evaluated for LVAD and RVAD support in cadaveric animal and human hearts attached to a MCL. LVAD inflow cannulation was achieved in under two minutes with the suture-less fixation device. No leakage through the suture-less fixation device – myocardial interface was noted. Continued development and in-vivo evaluation of this device may result in an improved inflow cannulation technique with the potential for off-bypass insertion. Continued development of this research, in particular the compliant inflow cannula and suture-less inflow cannulation device, will result in improved postoperative outcomes, life span and quality of life for end-stage heart failure patients.