Learning Latent Super-Events to Detect Multiple Activities in Videos

In this paper, we introduce the concept of learning latent super-events from activity videos, and present how it benefits activity detection in continuous videos. We define a super-event as a set of multiple events occurring together in videos with a particular temporal organization; it is the opposite concept of sub-events. Real-world videos contain multiple activities and are rarely segmented (e.g., surveillance videos), and learning latent super-events allows the model to capture how the events are temporally related in videos. We design temporal structure filters that enable the model to focus on particular sub-intervals of the videos, and use them together with a soft attention mechanism to learn representations of latent super-events. Super-event representations are combined with per-frame or per-segment CNNs to provide frame-level annotations. Our approach is designed to be fully differentiable, enabling end-to-end learning of latent super-event representations jointly with the activity detector using them. Our experiments with multiple public video datasets confirm that the proposed concept of latent super-event learning significantly benefits activity detection, advancing the state-of-the-arts.Comment: CVPR 201

FutureGRID: A Program for long-term research into GRID systems architecture

Proceedings of the 2003 UK e-Science All Hands Meeting, 31st August - 3rd September, Nottingham UKThis is a project to carry out research into long-term GRID architecture, in the University of Cambridge Computer Laboratory and the Cambridge eScience Center, with support from the Microsoft Research Laboratory, Cambridge. It is part of a larger vision for future systems architectures for public computing platforms, including both scientitic GRID and commodity level computing such as games, peer2peer computing and storage services and so forth, based on work in the laboratories in recent years into massively scaleable distributed systems for storage, computation, content distribution and collaboration[26]

Irish drug abusers II: their psychological characteristics.

This is the second in a series of 3 articles based on a study of a cohort of Irish drug abusers. This article attempts to identify the psychological traits of drug abusers within the cohort. The cohort consists of 100 drug abusers who attend a drug advisory and treatment centre in Dublin for the first time between November 1977 and February 1979. Three psychosocial, scales (GEFT, NSQ, and PFS) were administered to each subject. Overall, the results indicate that subjects who participated in the study, while of average or above average intelligence, were poorly psychologically adjusted, characterised by a poor sense of identity, a high level of suggestibility and a tendency towards emotional dependence. Their overall level of intelligence was within or above the normal range