Review of Person Re-identification Techniques

Person re-identification across different surveillance cameras with disjoint fields of view has become one of the most interesting and challenging subjects in the area of intelligent video surveillance. Although several methods have been developed and proposed, certain limitations and unresolved issues remain. In all of the existing re-identification approaches, feature vectors are extracted from segmented still images or video frames. Different similarity or dissimilarity measures have been applied to these vectors. Some methods have used simple constant metrics, whereas others have utilised models to obtain optimised metrics. Some have created models based on local colour or texture information, and others have built models based on the gait of people. In general, the main objective of all these approaches is to achieve a higher-accuracy rate and lowercomputational costs. This study summarises several developments in recent literature and discusses the various available methods used in person re-identification. Specifically, their advantages and disadvantages are mentioned and compared.Comment: Published 201

Machine Learning for Large-Scale Quality Control of 3D Shape Models in Neuroimaging.

As very large studies of complex neuroimaging phenotypes become more common, human quality assessment of MRI-derived data remains one of the last major bottlenecks. Few attempts have so far been made to address this issue with machine learning. In this work, we optimize predictive models of quality for meshes representing deep brain structure shapes. We use standard vertex-wise and global shape features computed homologously across 19 cohorts and over 7500 human-rated subjects, training kernelized Support Vector Machine and Gradient Boosted Decision Trees classifiers to detect meshes of failing quality. Our models generalize across datasets and diseases, reducing human workload by 30-70%, or equivalently hundreds of human rater hours for datasets of comparable size, with recall rates approaching inter-rater reliability

Physicians' guideline adherence is associated with long-term heart failure mortality in outpatients with heart failure with reduced ejection fraction: the QUALIFY international registry

Background: Physicians' adherence to guideline-recommended therapy is associated with short-term clinical outcomes in heart failure (HF) with reduced ejection fraction (HFrEF). However, its impact on longer-term outcomes is poorly documented. Here, we present results from the 18-month follow-up of the QUALIFY registry. Methods and results: Data at 18 months were available for 6118 ambulatory HFrEF patients from this international prospective observational survey. Adherence was measured as a continuous variable, ranging from 0 to 1, and was assessed for five classes of recommended HF medications and dosages. Most deaths were cardiovascular (CV) (228/394) and HF-related (191/394) and the same was true for unplanned hospitalizations (1175 CV and 861 HF-related hospitalizations, out of a total of 1541). According to univariable analysis, CV and HF deaths were significantly associated with physician adherence to guidelines. In multivariable analysis, HF death was associated with adherence level [subdistribution hazard ratio (SHR) 0.93, 95% confidence interval (CI) 0.87–0.99 per 0.1 unit adherence level increase; P = 0.034] as was composite of HF hospitalization or CV death (SHR 0.97, 95% CI 0.94–0.99 per 0.1 unit adherence level increase; P = 0.043), whereas unplanned all-cause, CV or HF hospitalizations were not (all-cause: SHR 0.99, 95% CI 0.9–1.02; CV: SHR 0.98, 95% CI 0.96–1.01; and HF: SHR 0.99, 95% CI 0.96–1.02 per 0.1 unit change in adherence score; P = 0.52, P = 0.2, and P = 0.4, respectively). Conclusion: These results suggest that physicians' adherence to guideline-recommended HF therapies is associated with improved outcomes in HFrEF. Practical strategies should be established to improve physicians' adherence to guidelines. © 2019 The Authors. European Journal of Heart Failure © 2019 European Society of Cardiolog