Crowd Counting Using Multiple Local Features

In public venues, crowd size is a key indicator of crowd safety and stability. Crowding levels can be detected using holistic image features, however this requires a large amount of training data to capture the wide variations in crowd distribution. If a crowd counting algorithm is to be deployed across a large number of cameras, such a large and burdensome training requirement is far from ideal. In this paper we propose an approach that uses local features to count the number of people in each foreground blob segment, so that the total crowd estimate is the sum of the group sizes. This results in an approach that is scalable to crowd volumes not seen in the training data, and can be trained on a very small data set. As a local approach is used, the proposed algorithm can easily be used to estimate crowd density throughout different regions of the scene and be used in a multi-camera environment. A unique localised approach to ground truth annotation reduces the required training data is also presented, as a localised approach to crowd counting has different training requirements to a holistic one. Testing on a large pedestrian database compares the proposed technique to existing holistic techniques and demonstrates improved accuracy, and superior performance when test conditions are unseen in the training set, or a minimal training set is used.

Generating Flash files of Your Lectures: Good Practice Strategies Helping Students Engage with Their Learning

Our students come from diverse backgrounds. They need flexibility in their learning. First year students tend to worry when they miss lectures or part of lectures. Having the lecture as an on line resource allows students to miss a lecture without stressing about it and to be more relaxed in the lecture, knowing that anything they may miss will be available later. The resource: The Windows based program from Blueberry Software (not Blackberry!) - BB Flashback - allows the simultaneous recording of the computer screen together with the audio, as well as Webcam recording. Editing capabilities include adding pause buttons, graphics and text to the file before exporting it in a flash file. Any diagrams drawn on the board or shown via visualiser can be photographed and easily incorporated. The audio from the file can be extracted if required to be posted as podcast. Exporting modes other than Flash are also available, allowing vodcasting if you wish. What you will need: - the recording software: it can be installed on the lecture hall computer just prior to lecture if needed - a computer: either the ones in lecture halls, especially if fitted with audio recording, or a laptop (I have used audio recording via Bluetooth for mobility). Feedback from students has been positive and will be presented on the poster.

Bit-pattern based integral attack

Integral attacks are well-known to be effective against byte-based block ciphers. In this document, we outline how to launch integral attacks against bit-based block ciphers. This new type of integral attack traces the propagation of the plaintext structure at bit-level by incorporating bit-pattern based notations. The new notation gives the attacker more details about the properties of a structure of cipher blocks. The main difference from ordinary integral attacks is that we look at the pattern the bits in a specific position in the cipher block has through the structure. The bit-pattern based integral attack is applied to Noekeon, Serpent and present reduced up to 5, 6 and 7 rounds, respectively. This includes the first attacks on Noekeon and present using integral cryptanalysis. All attacks manage to recover the full subkey of the final round.

Scene invariant crowd counting for real-time surveillance

Automated crowd counting allows excessive crowding to be detected immediately, without the need for constant human surveillance. Current crowd counting systems are location specific, and for these systems to function properly they must be trained on a large amount of data specific to the target location. As such, configuring multiple systems to use is a tedious and time consuming exercise. We propose a scene invariant crowd counting system which can easily be deployed at a different location to where it was trained. This is achieved using a global scaling factor to relate crowd sizes from one scene to another. We demonstrate that a crowd counting system trained at one viewpoint can achieve a correct classification rate of 90% at a different viewpoint.

Use of IP addresses for high rate flooding attack detection

High-rate flooding attacks (aka Distributed Denial of Service or DDoS attacks) continue to constitute a pernicious threat within the Internet domain. In this work we demonstrate how using packet source IP addresses coupled with a change-point analysis of the rate of arrival of new IP addresses may be sufficient to detect the onset of a high-rate flooding attack. Importantly, minimizing the number of features to be examined, directly addresses the issue of scalability of the detection process to higher network speeds. Using a proof of concept implementation we have shown how pre-onset IP addresses can be efficiently represented using a bit vector and used to modify a “white list” filter in a firewall as part of the mitigation strategy.

Crowd counting using group tracking and local features

In public venues, crowd size is a key indicator of crowd safety and stability. In this paper we propose a crowd counting algorithm that uses tracking and local features to count the number of people in each group as represented by a foreground blob segment, so that the total crowd estimate is the sum of the group sizes. Tracking is employed to improve the robustness of the estimate, by analysing the history of each group, including splitting and merging events. A simplified ground truth annotation strategy results in an approach with minimal setup requirements that is highly accurate.

Attack of the creationist reverberators! Or: the end of the world (as we know it)

This special issue of Popular Communication examines the impact of the global financial crisis and recession on differnt aspects of global and regional media and the cultural industries, changing practices of media production, as well as media consumption, and the interplay of economic challenges and technological change.

Alone against the crowd: Individual differences in referees' ability to cope under pressure

This paper contributes to the recent debate about the role of referees in the home advantage phenomenon. Specifically, it aims to provide a convincing answer to the newly posed question of the existence of individual differences among referees in terms of the home advantage (Boyko, Boyko, & Boyko, 2007; Johnston, 2008). Using multilevel modelling on a large and representative dataset we find that (1) the home advantage effect differs significantly among referees, and (2) this relationship is moderated by the size of the crowd. These new results suggest that a part of the home advantage is due to the effect of the crowd on the referees, and that some referees are more prone to be influenced by the crowd than others. This provides strong evidence to indicate that referees are a significant contributing factor to the home advantage. The implications of these findings are discussed both in terms of the relevant social psychological research, and with respect to the selection, assessment, and training of referees.

Scene invariant crowd counting

This paper describes a scene invariant crowd counting algorithm that uses local features to monitor crowd size. Unlike previous algorithms that require each camera to be trained separately, the proposed method uses camera calibration to scale between viewpoints, allowing a system to be trained and tested on different scenes. A pre-trained system could therefore be used as a turn-key solution for crowd counting across a wide range of environments. The use of local features allows the proposed algorithm to calculate local occupancy statistics, and Gaussian process regression is used to scale to conditions which are unseen in the training data, also providing confidence intervals for the crowd size estimate. A new crowd counting database is introduced to the computer vision community to enable a wider evaluation over multiple scenes, and the proposed algorithm is tested on seven datasets to demonstrate scene invariance and high accuracy. To the authors' knowledge this is the first system of its kind due to its ability to scale between different scenes and viewpoints.

Scene invariant crowd counting and crowd occupancy analysis

In public places, crowd size may be an indicator of congestion, delay, instability, or of abnormal events, such as a fight, riot or emergency. Crowd related information can also provide important business intelligence such as the distribution of people throughout spaces, throughput rates, and local densities. A major drawback of many crowd counting approaches is their reliance on large numbers of holistic features, training data requirements of hundreds or thousands of frames per camera, and that each camera must be trained separately. This makes deployment in large multi-camera environments such as shopping centres very costly and difficult. In this chapter, we present a novel scene-invariant crowd counting algorithm that uses local features to monitor crowd size. The use of local features allows the proposed algorithm to calculate local occupancy statistics, scale to conditions which are unseen in the training data, and be trained on significantly less data. Scene invariance is achieved through the use of camera calibration, allowing the system to be trained on one or more viewpoints and then deployed on any number of new cameras for testing without further training. A pre-trained system could then be used as a ‘turn-key’ solution for crowd counting across a wide range of environments, eliminating many of the costly barriers to deployment which currently exist.

Problem-solving courts, therapeutic jurisprudence and the constitution : if two is company, is three a crowd?

Court costs, resource-intensive trials, booming prison populations and the obduracy of recidivism rates all present as ugly excesses of the criminal law adversarial paradigm. To combat these excesses, problem-solving courts have evolved with an edict to address the underlying issues that have caused an individual to commit a crime. When a judge seeks to help a problem-solving court participant deal with issues like addiction, mental health or poverty, they are performing a very different role to that of a judicial officer in the traditional court hierarchy. They are no longer the removed, independent arbiter — a problem-solving court judge steps into the ‘arena’ with the participant and makes active use of their judicial authority to assist in rehabilitation and positive behavioural change. Problem-solving court judges employing the principles of therapeutic jurisprudence appreciate that their interaction with participants can have therapeutic and anti-therapeutic consequences. This article will consider how the deployment of therapeutic measures (albeit with good intention) can lead to the behavioural manifestation of partiality and bias on the part of problem-solving court judges. Chapter III of the Commonwealth Constitution will then be analysed to highlight why the operation and functioning of problem solving courts may be deemed unconstitutional. Part IV of this article will explain how a problem-solving court judge who is not acting impartially or independently will potentially contravene the requirements of the Constitution. It will finally be suggested that judges who possess a high level of emotional intelligence will be the most successful in administering an independent and impartial problem solving court.

Where not to have a Heart Attack in Australia!: The Cardiac ARIA Index

Background/aims: Access to appropriate health care following an acute cardiac event is important for positive outcomes. The aim of the Cardiac ARIA index was to derive an objective, comparable, geographic measure reflecting access to cardiac services across Australia. Methods: Geographic Information Systems (GIS) were used to model a numeric-alpha index based on acute management from onset of symptoms to return to the community. Acute time frames have been calculated to include time for ambulance to arrive, assess and load patient, and travel to facility by road 40–80 kph. Results: The acute phase of the index was modelled into five categories: 1 [24/7 percutaneous cardiac intervention (PCI) ≤1 h]; 2 [24/7 PCI 1–3 h, and PCI less than an additional hour to nearest accident and emergency room (A&E)]: 3 [Nearest A&E ≤3 h (no 24/7 PCI within an extra hour)]: 4 [Nearest A&E 3–12 h (no 24/7 PCI within an extra hour)]: 5 [Nearest A&E 12–24 h (no 24/7 PCI within an extra hour)]. Discharge care was modelled into three categories based on time to a cardiac rehabilitation program, retail pharmacy, pathology services, hospital, GP or remote clinic: (A) all services ≤30 min; (B) >30 min and ≤60 min; (C) >60 min. Examples of the index indicate that the majority of population locations within capital cities were category 1A; Alice Springs and Byron Bay were 3A; and the Northern Territory town of Maningrida had minimal access to cardiac services with an index ranking of 5C. Conclusion: The Cardiac ARIA index provides an invaluable tool to inform appropriate strategies for the use of scarce cardiac resources.

Early local functional changes in the human diabetic retina : a global flash multifocal electroretinogram study

Purpose: To investigate early functional changes of local retinal defects in type II diabetic patients using the global flash multifocal electroretinogram (MOFO mfERG). Methods: Thirty-eight diabetic patients and 14 age-matched controls were recruited. Nine of the diabetics were free from diabetic retinopathy (DR), while the remainder had mild to moderate non-proliferative diabetic retinopathy. The MOFO mfERG was performed at high (98%) and low (46%) contrast levels. MfERG responses were grouped into 35 regions for comparison with DR classification at those locations. Z-scores of the regional mfERG responses were compared across different types of DR defects. Results: The mfERG waveform consisted of the direct component (DC) and the induced component (IC). Local reduction in DC and IC amplitudes were found in diabetic patients with and without DR. With increasing severity of retinopathy, there was a further deterioration in amplitude of both components. Under MOFO mfERG paradigm, amplitude was a useful screening parameter. Conclusion: The MOFO mfERG can help in detecting early functional anomalies before the appearance of visible signs, and may assist in monitoring further functional deterioration in diabetic patients.

An attack on Iran: the legal basis, or lack thereof

Talk of a possible Israeli strike on Iran’s nuclear facilities has re-ignited debate over the right of self-defence under international law. Some academics, including Anthony D'Amato and Alan Dershowitz, have claimed that an attack on Iran would be a permissible act of self-defence. Others, such as Kevin Jon Heller, argue that such action would be a clear breach of international law. So, who is correct? Would military action against Iran be legal or illegal?