Robust visual tracking using structurally random projection and weighted least squares

Sparse representation based visual tracking approaches have attracted increasing interests in the community in recent years. The main idea is to linearly represent each target candidate using a set of target and trivial templates while imposing a sparsity constraint onto the representation coefficients. After we obtain the coefficients using L1-norm minimization methods, the candidate with the lowest error, when it is reconstructed using only the target templates and the associated coefficients, is considered as the tracking result. In spite of promising system performance widely reported, it is unclear if the performance of these trackers can be maximised. In addition, computational complexity caused by the dimensionality of the feature space limits these algorithms in real-time applications. In this paper, we propose a real-time visual tracking method based on structurally random projection and weighted least squares techniques. In particular, to enhance the discriminative capability of the tracker, we introduce background templates to the linear representation framework. To handle appearance variations over time, we relax the sparsity constraint using a weighed least squares (WLS) method to obtain the representation coefficients. To further reduce the computational complexity, structurally random projection is used to reduce the dimensionality of the feature space while preserving the pairwise distances between the data points in the feature space. Experimental results show that the proposed approach outperforms several state-of-the-art tracking methods.

Tracking Change in Northern Ireland Policing: Temporal Phases and Key Themes

Purpose
– The purpose of this paper is to explore and explain the change process in Northern Ireland policing through an analysis of temporally bracketed change phases and key change delivery themes ranging from 1996 to 2012.

Design/methodology/approach
– The research approach adopted is process based, longitudinal and multi-method, utilising “temporal bracketing” to determine phases of change and conjunctural reasoning to unravel the systematic factors interacting over time, within the case.

Findings
– The paper identifies and temporally brackets four phases of change: “Tipping point”; “Implementation, Symbolic Modification and Resistance”; “Power Assisted Steering”; and “A Return to Turbulence”, identifies four themes that emerge from RUC-PSNI experience: the role of adaptive leadership; pace and sequencing of change implementation; sufficient resourcing; and the impact of external agents acting as boundary spanners, and comments on the prominence of these themes through the phases. The paper goes on to reflect upon how these phases and themes inform our understanding of organisational change within policing organisations generally and within politically pressurised transition processes.

Originality/value
– The contribution of the paper lies in the documentation of an almost unique organisational case in an environmentally forced change process. In this it contains lessons for other organisations facing similar, if less extreme challenges and presents an example of intense change analysed longitudinally.

Tracking smart grid hackers

The next-generation smart grid will rely highly on telecommunications infrastructure for data transfer between various systems. Anywhere we have data transfer in a system is a potential security threat. When we consider the possibility of smart grid data being at the heart of our critical systems infrastructure it is imperative that we do all we can to ensure the confidentiality, availability and integrity of the data. A discussion on security itself is outside the scope of this paper, but if we assume the network to be as secure as possible we must consider what we can do to detect when that security fails, or when the attacks comes from the inside of the network. One way to do this is to setup a hacker-trap, or honeypot. A honeypot is a device or service on a network which appears legitimate, but is in-fact a trap setup to catch breech attempts. This paper identifies the different types of honeypot and describes where each may be used. The authors have setup a test honeypot system which has been live for some time. The test system has been setup to emulate a device on a utility network. The system has had many hits, which are described in detail by the authors. Finally, the authors discuss how larger-scale systems in utilities may benefit from honeypot placement.

Visual attention to food cues in obesity: An eye‐tracking study.

Objective
Based on the theory of incentive sensitization, the aim of this study was to investigate differences in attentional processing of food-related visual cues between normal-weight and overweight/obese males and females.

Methods
Twenty-six normal-weight (14M, 12F) and 26 overweight/obese (14M, 12F) adults completed a visual probe task and an eye-tracking paradigm. Reaction times and eye movements to food and control images were collected during both a fasted and fed condition in a counterbalanced design.

Results
Participants had greater visual attention towards high-energy-density food images compared to low-energy-density food images regardless of hunger condition. This was most pronounced in overweight/obese males who had significantly greater maintained attention towards high-energy-density food images when compared with their normal-weight counterparts however no between weight group differences were observed for female participants.

Conclusions
High-energy-density food images appear to capture visual attention more readily than low-energy-density food images. Results also suggest the possibility of an altered visual food cue-associated reward system in overweight/obese males. Attentional processing of food cues may play a role in eating behaviors thus should be taken into consideration as part of an integrated approach to curbing obesity.

Modulation Insensitive PLL for Tracking Antenna Applications

This article shows practical results of a self-tracking receiving antenna array using a new phase locked loop (PLL) tracking configuration. The PLL configuration differs from other architectures, as it has the new feature of being able to directly track phase modulated signals without requiring an additional unmodulated pilot carrier to be present. The PLLs are used within the antenna array to produce a constant phase intermediate frequency (IF) for each antenna element. These IF's can then be combined in phase, regardless of the angle of arrival of the signal, thus utilizing the antennas array factor. The article's main focus is on the phase jitter performance of the modulation insensitive PLL carrier recovery when tracking phase modulated signals of low signal to noise ratio. From this analysis, it is concluded that the new architecture, when optimally designed, can produce phase jitter performance close to that of a conventional tracking PLL.

Enhancing Linear Programming with Motion Modeling for Multi-target Tracking

In this paper we extend the minimum-cost network flow approach to multi-target tracking, by incorporating a motion model, allowing the tracker to better cope with longterm occlusions and missed detections. In our new method, the tracking problem is solved iteratively: Firstly, an initial tracking solution is found without the help of motion information. Given this initial set of tracklets, the motion at each detection is estimated, and used to refine the tracking solution.
Finally, special edges are added to the tracking graph, allowing a further revised tracking solution to be found, where distant tracklets may be linked based on motion similarity. Our system has been tested on the PETS S2.L1 and Oxford town-center sequences, outperforming the baseline system, and achieving results comparable with the current state of the art.

Localization Algorithm Performance in Ultra Low Power Active RFID Based Patient Tracking

Indoor personnel localization research has generated a range of potential techniques and algorithms. However, these typically do not account for the influence of the user's body upon the radio channel. In this paper an active RFID based patient tracking system is demonstrated and three localization algorithms are used to estimate the location of a user within a modern office building. It is shown that disregarding body effects reduces the accuracy of the algorithms' location estimates and that body shadowing effects create a systematic position error that estimates the user's location as closer to the RFID reader that the active tag has line of sight to.

Asset Tracking in Critical Power Communications Infrastructures using Passive Techniques

Active network scanning injects traffic into a network and observes responses to draw conclusions about the network. Passive network analysis works by looking at network meta data or by analyzing traffic as it traverses a fixed point on the network. It may be infeasible or inappropriate to scan critical infrastructure networks. Techniques exist to uniquely map assets without resorting to active scanning. In many cases, it is possible to characterize and identify network nodes by passively analyzing traffic flows. These techniques are considered in particular with respect to their application to power industry critical infrastructure.

Identification and output tracking control of Hammerstein systems through wireless networks

his paper investigates the identification and output tracking control of a class of Hammerstein systems through a wireless network within an integrated framework and the statistic characteristics of the wireless network are modelled using the inverse Gaussian cumulative distribution function. In the proposed framework, a new networked identification algorithm is proposed to compensate for the influence of the wireless network delays so as to acquire the more precise Hammerstein system model. Then, the identified model together with the model-based approach is used to design an output tracking controller. Mean square stability conditions are given using linear matrix inequalities (LMIs) and the optimal controller gains can be obtained by solving the corresponding optimization problem expressed using LMIs. Illustrative numerical simulation examples are given to demonstrate the effectiveness of our proposed method.

Alcohol attention bias in adolescent social drinkers: an eye tracking study

Rationale
Previous research on attention bias in nondependent social drinkers has focused on adult samples with limited focus on the presence of attention bias for alcohol cues in adolescent social drinkers.
Objectives
The aim of this study was to examine the presence of alcohol attention bias in adolescents and the relationship of this cognitive bias to alcohol use and alcohol-related expectancies.
Methods
Attention bias in adolescent social drinkers and abstainers was measured using an eye tracker during exposure to alcohol and neutral cues. Questionnaires measured alcohol use and explicit alcohol expectancies.
Results
Adolescent social drinkers spent significantly more time fixating to alcohol stimuli compared to controls. Total fixation time to alcohol stimuli varied in accordance with level of alcohol consumption and was significantly associated with more positive alcohol expectancies. No evidence for automatic orienting to alcohol stimuli was found in adolescent social drinkers.
Conclusion
Attention bias in adolescent social drinkers appears to be underpinned by controlled attention suggesting that whilst participants in this study displayed alcohol attention bias comparable to that reported in adult studies, the bias has not developed to the point of automaticity. Initial fixations appeared to be driven by alternative attentional processes which are discussed further.

The use of eye-tracking to explore social difficulties in cognitively able students with autism spectrum disorder: A pilot study

Individuals with autism spectrum disorder do not just 'grow out of' their early difficulties in understanding the social world. Even for those who are cognitively able, autism-related difficulties continue into adulthood. Atypicalities attending to and interpreting communicative signals from others can provide barriers to success in education, employment and relationships. In the current study, we use eye-tracking during real social interaction to explore attention to social cues (e.g. face, eyes, mouth) and links to social awareness in a group of cognitively able University students with autism spectrum disorder and typically developing students from the same University. During the interaction, students with autism spectrum disorder showed less eye fixation and more mouth fixation than typically developing students. Importantly, while 63% of typically developing participants reported thinking they were deceived about the true nature of the interaction, only 9% of autism spectrum disorder participants picked up this subtle social signal. We argue that understanding how these social attentional and social awareness difficulties manifest during adulthood is important given the growing number of adults with autism spectrum disorder who are attending higher level education. These adults may be particularly susceptible to drop-out due to demands of coping in situations where social awareness is so important.

Obsessive-compulsive symptoms and attentional bias: An eye-tracking methodology

Background and objectives: Cognitive models suggest that attentional biases are integral in the maintenance of obsessive-compulsive symptoms (OCS). Such biases have been established experimentally in anxiety disorders; however, the evidence is unclear in Obsessive Compulsive disorder (OCD). In the present study, an eye-tracking methodology was employed to explore attentional biases in relation to OCS.
Methods: A convenience sample of 85 community volunteers was assessed on OCS using the Yale-Brown Obsessive Compulsive Scale-self report. Participants completed an eye-tracking paradigm where they were exposed to OCD, Aversive and Neutral visual stimuli. Indices of attentional bias were derived from the eye-tracking data.
Results: Simple linear regressions were performed with OCS severity as the predictor and eye-tracking measures of the different attentional biases for each of the three stimuli types were the criterion variables. Findings revealed that OCS severity moderately predicted greater frequency and duration of fixations on OCD stimuli, which reflect the maintenance attentional bias. No significant results were found in support of other biases.
Limitations: Interpretations based on a non-clinical sample limit the generalisability of the conclusions, although use of such samples in OCD research has been found to be comparable to clinical populations. Future research would include both clinical and sub-clinical participants.
Conclusions: Results provide some support for the theory of maintained attention in OCD attentional biases, as opposed to vigilance theory. Individuals with greater OCS do not orient to OCD stimuli any faster than individuals with lower OCS, but once a threat is identified, these individuals allocate more attention to OCS-relevant stimuli.

A Novel Semi-Automated Method of Tracking Fetal Movements

We have designed software that can â€â€™look’’ at recorded ultrasound sequences. We analyzed fifteen video sequences representing recorded ultrasound scans of nine fetuses. Our method requires a small amount of user labelled pixels for processing the first frame. These initialize GrowCut 1 , a background removal algorithm, which was used for separating the fetus from its surrounding environment (segmentation). For each subsequent frame, user input is no longer necessary as some of the pixels will inherit labels from the previously processed frame. This results in our software’s ability to track movement. Two sonographers rated the results of our computer’s â€vision’ on a scale from 1 (poor fit) to 10 (excellent fit). They assessed tracking accuracy for the entire video as well as segmentation accuracy (the ability to identify fetus from non-fetus) for every 100th processed frame. There was no appreciable deterioration in the software’s ability to track the fetus over time. I