Activity recognition using binary tree SVM

This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.

Consensus statement on the role of Accredited Exercise Physiologists within the treatment of mental disorders: A guide for mental health professionals

- Objective The aim is to identify the role and scope of Accredited Exercise Physiologist (AEP) services in the mental health sector and to provide insight as to how AEPs can contribute to the multidisciplinary mental health team. - Methods A modified Delphi approach was utilised. Thirteen AEPs with experience in mental health contributed to the iterative development of a national consensus statement. Six mental health professionals with expertise in psychiatry, mental health nursing, general practice and mental health research participated in the review process. Reviewers were provided with a template to systematically provide feedback on the language, content, structure and relevance to their professional group. - Results This consensus statement outlines how AEPs can contribute to the multidisciplinary mental health team, the aims and scope of AEP-led interventions in mental health services and examples of such interventions, the range of physical and mental health outcomes possible through AEP-led interventions and common referral pathways to community AEP services. - Outcome AEPs can play a key role in the treatment of individuals experiencing mental illness. The diversity of AEP interventions allows for a holistic approach to care, enhancing both physical and mental health outcomes.

Comment on “Whole-genome analyses resolve early branches in the tree of life of modern birds”

Jarvis et al. (Research Articles, 12 December 2014, p. 1320) presented molecular clock analyses that suggested that most modern bird orders diverged just after the mass extinction event at the Cretaceous-Paleogene boundary (about 66 million years ago). We demonstrate that this conclusion results from the use of a single inappropriate maximum bound, which effectively precludes the Cretaceous diversification overwhelmingly supported by previous molecular studies.