Gaussian Approximation for Tracking Occluding and Interacting Targets

In this paper, we show how interacting and occluding targets can be tackled successfully within a Gaussian approximation. For that purpose, we develop a general expansion of the mean and covariance of the posterior and we consider a first order approximation of it. The proposed method differs from EKF in that neither a non-linear dynamical model nor a non-linear measurement vector to state relation have to be defined, so it works with any kind of interaction potential and likelihood. The approach has been tested on three sequences (10400, 2500, and 400 frames each one). The results show that our approach helps to reduce the number of failures without increasing too much the computation time with respect to methods that do not take into account target interactions.

Tracking the Links to Social Functioning: Asperger Syndrome and Gaze Patterns

The application of Eye Tracking (ET) to the study of social functioning in Asperger Syndrome (AS) provides a unique perspective into social attention and cognition in this atypical neurodevelopmental group. Research in this area has shown how ET can capture social attention atypicalities within this group, such as diminished fixations to the eye region when viewing still images and movie clips; increased fixation to the mouth region; reduced face gaze. Issues exist, however, within the literature, where the type (static/dynamic) and the content (ecological validity) of stimuli used appear to affect the nature of the gaze patterns reported. Objectives: Our research aims were: using the same group of adolescents with AS, to compare their viewing patterns to age and IQ matched typically developing (TD) adolescents using stimuli considered to represent a hierarchy of ecological validity, building from static facial images; through a non-verbal movie clip; through verbal footage from real-life conversation; to eye tracking during real-life conversation. Methods: Eleven participants with AS were compared to 11 TD adolescents, matched for age and IQ. In Study 1, participants were shown 2 sets of static facial images (emotion faces, still images taken from the dynamic clips). In Study 2, three dynamic clips were presented (1 non-verbal movie clip, 2 verbal footage from real-life conversation). Study 3 was an exploratory study of eye tracking during a real-life conversation. Eye movements were recorded via a HiSpeeed (240Hz) SMI eye tracker fitted with chin and forehead rests. Various methods of analysis were used, including a paradigm for temporal analysis of the eye movement data. Results: Results from these studies confirmed that the atypical nature of social attention in AS was successfully captured by this paradigm. While results differed across stimulus sets,
collectively they demonstrated how individuals with AS failed to focus on the most socially relevant aspects of the various stimuli presented. There was also evidence that the eye movements of the AS group were atypically affected by the presence of motion and verbal information. Discriminant Function Analysis demonstrated that the ecological validity of stimuli was an important factor in identifying atypicalities associated with AS, with more accurate classifications of AS and TD groups occurring for more naturalistic stimuli (dynamic rather than static). Graphical analysis of temporal sequences of eye movements revealed the atypical manner in which AS participants followed interactions within the dynamic stimuli. Taken together with data on the order of gaze patterns, more subtle atypicalities were detected in the gaze behaviour of AS individuals towards more socially pertinent regions of the dynamic stimuli. Conclusions: These results have potentially important implications for our understanding of deficits in Asperger Syndrome, as they show that, with more naturalistic stimuli, subtle differences in social attention can be detected that

Online Multiperson Tracking With Occlusion Reasoning and Unsupervised Track Motion Model

We address the problem of multi-target tracking in realistic crowded conditions by introducing a novel dual-stage online tracking algorithm. The problem of data-association between tracks and detections, based on appearance, is often complicated by partial occlusion. In the first stage, we address the issue of occlusion with a novel method of robust data-association, that can be used to compute the appearance similarity between tracks and detections without the need for explicit knowledge of the occluded regions. In the second stage, broken tracks are linked based on motion and appearance, using an online-learned linking model. The online-learned motion-model for track linking uses the confident tracks from the first stage tracker as training examples. The new approach has been tested on the town centre dataset and has performance comparable with the present state-of-the-art

Establishing optimal quantitative-polymerase chain reaction assays for routine diagnosis and tracking of minimal residual disease in JAK2-V617F-associated myeloproliferative neoplasms:a joint European LeukemiaNet/MPN&MPNr-EuroNet (COST action BM0902) study

Reliable detection of JAK2-V617F is critical for accurate diagnosis of myeloproliferative neoplasms (MPNs); in addition, sensitive mutation-specific assays can be applied to monitor disease response. However, there has been no consistent approach to JAK2-V617F detection, with assays varying markedly in performance, affecting clinical utility. Therefore, we established a network of 12 laboratories from seven countries to systematically evaluate nine different DNA-based quantitative PCR (qPCR) assays, including those in widespread clinical use. Seven quality control rounds involving over 21,500 qPCR reactions were undertaken using centrally distributed cell line dilutions and plasmid controls. The two best-performing assays were tested on normal blood samples (n=100) to evaluate assay specificity, followed by analysis of serial samples from 28 patients transplanted for JAK2-V617F-positive disease. The most sensitive assay, which performed consistently across a range of qPCR platforms, predicted outcome following transplant, with the mutant allele detected a median of 22 weeks (range 6-85 weeks) before relapse. Four of seven patients achieved molecular remission following donor lymphocyte infusion, indicative of a graft vs MPN effect. This study has established a robust, reliable assay for sensitive JAK2-V617F detection, suitable for assessing response in clinical trials, predicting outcome and guiding management of patients undergoing allogeneic transplant.

Generalized Laplacian Eigenmaps for Modeling and Tracking Human Motions

This paper presents generalized Laplacian eigenmaps, a novel dimensionality reduction approach designed to address stylistic variations in time series. It generates compact and coherent continuous spaces whose geometry is data-driven. This paper also introduces graph-based particle filter, a novel methodology conceived for efficient tracking in low dimensional space derived from a spectral dimensionality reduction method. Its strengths are a propagation scheme, which facilitates the prediction in time and style, and a noise model coherent with the manifold, which prevents divergence, and increases robustness. Experiments show that a combination of both techniques achieves state-of-the-art performance for human pose tracking in underconstrained scenarios.

Adaptive Fusion Of Particle Filtering And Spatio-Temporal Motion Energy For Human Tracking

Object tracking is an active research area nowadays due to its importance in human computer interface, teleconferencing and video surveillance. However, reliable tracking of objects in the presence of occlusions, pose and illumination changes is still a challenging topic. In this paper, we introduce a novel tracking approach that fuses two cues namely colour and spatio-temporal motion energy within a particle filter based framework. We conduct a measure of coherent motion over two image frames, which reveals the spatio-temporal dynamics of the target. At the same time, the importance of both colour and motion energy cues is determined in the stage of reliability evaluation. This determination helps maintain the performance of the tracking system against abrupt appearance changes. Experimental results demonstrate that the proposed method outperforms the other state of the art techniques in the used test datasets.

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.

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.

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.

Life history of turbot in Icelandic waters: Intra- and inter-population genetic diversity and otolith tracking of environmental temperatures

The stock structure of turbot was investigated between samples from S-Norway, the Irish Sea and the Kattegat, using 12 microsatellite loci and compared to the turbot caught in Icelandic waters. Highly significant genetic differentiation was observed between samples from Kattegat and other areas. Significant genetic differentiation was also observed between the Irish Sea sample on one hand and Iceland and S-Norway on the other hand. No significant genetic differentiation was observed between Iceland and S-Norway. Otoliths of 25 turbot, age ranging from 3 to 19 years, were subjected to nearly 300 mass spectrometry determinations of stable oxygen and carbon isotopes. Oxygen isotope composition (δ¹⁸O) in the otolith samples was used to estimate ambient temperature at time of otolith accretion, and yielded estimated temperatures experienced by the turbot ranging from 3 to 15°C. Overall, the genetic analysis indicates panmixia between turbot in Icelandic and Norwegian waters. While the extensive migration of larvae between Norway and Iceland is unlikely, passive drift of turbot larva from other areas (e.g. Ireland) cannot be ruled out. 

Use of negative information in positioning and tracking algorithms

To avoid additional hardware deployment, indoor localization systems have to be designed in such a way that they rely on existing infrastructure only. Besides the processing of measurements between nodes, localization procedure can include the information of all available environment information. In order to enhance the performance of Wi-Fi based localization systems, the innovative solution presented in this paper considers also the negative information. An indoor tracking method inspired by Kalman filtering is also proposed.

Entity localization and tracking: a sensor fusion-based mechanism in WSNs

Knowing exactly where a mobile entity is and monitoring its trajectory in real-time has recently attracted a lot of interests from both academia and industrial communities, due to the large number of applications it enables, nevertheless, it is nowadays one of the most challenging problems from scientific and technological standpoints. In this work we propose a tracking system based on the fusion of position estimations provided by different sources, that are combined together to get a final estimation that aims at providing improved accuracy with respect to those generated by each system individually. In particular, exploiting the availability of a Wireless Sensor Network as an infrastructure, a mobile entity equipped with an inertial system first gets the position estimation using both a Kalman Filter and a fully distributed positioning algorithm (the Enhanced Steepest Descent, we recently proposed), then combines the results using the Simple Convex Combination algorithm. Simulation results clearly show good performance in terms of the final accuracy achieved. Finally, the proposed technique is validated against real data taken from an inertial sensor provided by THALES ITALIA.