Visibility Constrained Generative Model for Depth-based 3D Facial Pose Tracking

In this paper, we propose a generative framework that unifies depth-based 3D facial pose tracking and face model adaptation on-the-fly, in the unconstrained scenarios with heavy occlusions and arbitrary facial expression variations. Specifically, we introduce a statistical 3D morphable model that flexibly describes the distribution of points on the surface of the face model, with an efficient switchable online adaptation that gradually captures the identity of the tracked subject and rapidly constructs a suitable face model when the subject changes. Moreover, unlike prior art that employed ICP-based facial pose estimation, to improve robustness to occlusions, we propose a ray visibility constraint that regularizes the pose based on the face model's visibility with respect to the input point cloud. Ablation studies and experimental results on Biwi and ICT-3DHP datasets demonstrate that the proposed framework is effective and outperforms completing state-of-the-art depth-based methods

Understanding the evaluation of access and participation outreach interventions for under 16 year olds

The project team was asked to address the following six research questions and these were used to guide the project: 1. What are the intended outcomes for current outreach interventions directed at under 16 year olds from disadvantaged backgrounds where the long-term aim is to widen access to higher education (HE)? 2. What types of outreach intervention activity or activities are institutions using in relation to intended outcomes? 3. What evaluation tools, methods and metrics are being used to measure the intended outcomes? 4. What are the perceived and actual challenges and barriers for different stakeholders to effective evaluation of long-term outreach? 5. What do different stakeholders consider most effective evaluation practice and why? 6. How valid and suitable are the evaluation tools, methods and metrics (identified through the research) that are commonly used? The project was constructed around six interlinked work packages: 1. A quantitative analysis of what higher education providers (HEPs) say about their pre-16 outreach activities (and their evaluation) in their 2017-18 access agreements (as the most recent available). 2. An online survey of HEPs to gather information about the pre-16 outreach activities delivered during the 2016-17 academic year and their evaluation, as well as the structure of their evaluation resources and challenges faced. 3. Case studies of four HEPs identified as demonstrating elements of good practice through their access agreements and the online survey, derived from telephone interviews with key staff and documentary analysis. 4. Telephone interviews with 11 third sector organisations (TSOs) to explore their practices and the evaluation of their activities, providing a counterpoint to the data collected from higher education institutions (HEIs). 5. A synthesis of the four preceding work packages to explore elements of good practice, determine a basis for assessing the quality of evaluations and highlight challenges for the sector and OFFA. 6. An invited participatory workshop for evaluators from HEPs and TSOs identified as demonstrating elements of good practice through the online survey and telephone interviews, to act as a sounding board for the emerging conclusions and recommendations.Office for Students (OfS

Quality Assessment for E-learning: a Benchmarking Approach (Third edition)

The primary purpose of this manual is to provide a set of benchmarks, quality criteria and notes for guidance against which e-learning programmes and their support systems may be judged. The manual should therefore be seen primarily as a reference tool for the assessment or review of e-learning programmes and the systems which support them. However, the manual should also prove to be useful to staff in institutions concerned with the design, development, teaching, assessment and support of e-learning programmes. It is hoped that course developers, teachers and other stakeholders will see the manual as a useful development and/or improvement tool for incorporation in their own institutional systems of monitoring, evaluation and enhancement

Event detection in field sports video using audio-visual features and a support vector machine

In this paper, we propose a novel audio-visual feature-based framework for event detection in broadcast video of multiple different field sports. Features indicating significant events are selected and robust detectors built. These features are rooted in characteristics common to all genres of field sports. The evidence gathered by the feature detectors is combined by means of a support vector machine, which infers the occurrence of an event based on a model generated during a training phase. The system is tested generically across multiple genres of field sports including soccer, rugby, hockey, and Gaelic football and the results suggest that high event retrieval and content rejection statistics are achievable

Snowmass CF1 Summary: WIMP Dark Matter Direct Detection

As part of the Snowmass process, the Cosmic Frontier WIMP Direct Detection subgroup (CF1) has drawn on input from the Cosmic Frontier and the broader Particle Physics community to produce this document. The charge to CF1 was (a) to summarize the current status and projected sensitivity of WIMP direct detection experiments worldwide, (b) motivate WIMP dark matter searches over a broad parameter space by examining a spectrum of WIMP models, (c) establish a community consensus on the type of experimental program required to explore that parameter space, and (d) identify the common infrastructure required to practically meet those goals.Comment: Snowmass CF1 Final Summary Report: 47 pages and 28 figures with a 5 page appendix on instrumentation R&

uC: Ubiquitous Collaboration Platform for Multimodal Team Interaction Support

A human-centered computing platform that improves teamwork and transforms the “human- computer interaction experience” for distributed teams is presented. This Ubiquitous Collaboration, or uC (“you see”), platform\u27s objective is to transform distributed teamwork (i.e., work occurring when teams of workers and learners are geographically dispersed and often interacting at different times). It achieves this goal through a multimodal team interaction interface realized through a reconfigurable open architecture. The approach taken is to integrate: (1) an intuitive speech- and video-centric multi-modal interface to augment more conventional methods (e.g., mouse, stylus and touch), (2) an open and reconfigurable architecture supporting information gathering, and (3) a machine intelligent approach to analysis and management of heterogeneous live and stored sensor data to support collaboration. The system will transform how teams of people interact with computers by drawing on both the virtual and physical environment