Towards robust 3D face recognition from noisy range images with low resolution

For a number of different security and industrial applications, there is the need for reliable person identification methods. Among these methods, face recognition has a number of advantages such as being non-invasive and potentially covert. Since the device for data acquisition is a conventional camera, other advantages of a 2D face recognition system are its low data capture duration and its low cost. However, the recent introduction of fast and comparatively inexpensive time-of-flight (TOF) cameras for the recording of 2.5D range data calls for a closer look at 3D face recognition in this context. One major disadvantage, however, is the low quality of the data aquired with such cameras. In this paper, we introduce a robust 3D face recognition system based on such noisy range images with low resolution

Assessing treatment outcomes in multiple sclerosis trials and in the clinical setting

Increasing numbers of drugs are being developed for the treatment of multiple sclerosis (MS). Measurement of relevant outcomes is key for assessing the efficacy of new drugs in clinical trials and for monitoring responses to disease-modifying drugs in individual patients. Most outcomes used in trial and clinical settings reflect either clinical or neuroimaging aspects of MS (such as relapse and accrual of disability or the presence of visible inflammation and brain tissue loss, respectively). However, most measures employed in clinical trials to assess treatment effects are not used in routine practice. In clinical trials, the appropriate choice of outcome measures is crucial because the results determine whether a drug is considered effective and therefore worthy of further development; in the clinic, outcome measures can guide treatment decisions, such as choosing a first-line disease-modifying drug or escalating to second-line treatment. This Review discusses clinical, neuroimaging and composite outcome measures for MS, including patient-reported outcome measures, used in both trials and the clinical setting. Its aim is to help clinicians and researchers navigate through the multiple options encountered when choosing an outcome measure. Barriers and limitations that need to be overcome to translate trial outcome measures into the clinical setting are also discussed