Proactive listening to a training commentary improves hazard prediction

The aim of this work was to explore the effect of Proactive Listening to a Training Commentary, using the recently developed version of the Spanish Hazard Perception test. Firstly, 16 videos were used in the pre-test session in its short version, cut to black just before the hazard appearance. The What Happens Next Assessment (at the pre-test stage) generates expectations about the outcome of the traffic situation. Then, the training (8 minutes in length) uses the complete version of the same 16 videos, revealing the hazards unfolding. It involves listening to a voice with relevant information about where to allocate attention in the complex driving scene in order to recognise and anticipate the hazard successfully. A total of 121 participants were included in this study The sample consisted of learner, novice and experienced drivers, including re-offender and non-offender drivers. The participants were divided into 2 groups: a trained and an untrained group. Two assessment times were used: pre-test (16 videos) and post-test sessions (another 16 videos). The test presented a high internal consistency (Alpha = 0.875). This training shows significant positive effects for all types and groups of participants. No significant differences were found between the non-offender and the offender groups. Performance in gradual-onset hazard events can be improved after training but also by practice; however this training is essential and especially beneficial for training the ability to detect hazards that appear abruptly (which seems to be difficult to improve just by practice)

Tencent AVS: A Holistic Ads Video Dataset for Multi-modal Scene Segmentation

Temporal video segmentation and classification have been advanced greatly by public benchmarks in recent years. However, such research still mainly focuses on human actions, failing to describe videos in a holistic view. In addition, previous research tends to pay much attention to visual information yet ignores the multi-modal nature of videos. To fill this gap, we construct the Tencent `Ads Video Segmentation'~(TAVS) dataset in the ads domain to escalate multi-modal video analysis to a new level. TAVS describes videos from three independent perspectives as `presentation form', `place', and `style', and contains rich multi-modal information such as video, audio, and text. TAVS is organized hierarchically in semantic aspects for comprehensive temporal video segmentation with three levels of categories for multi-label classification, e.g., `place' - `working place' - `office'. Therefore, TAVS is distinguished from previous temporal segmentation datasets due to its multi-modal information, holistic view of categories, and hierarchical granularities. It includes 12,000 videos, 82 classes, 33,900 segments, 121,100 shots, and 168,500 labels. Accompanied with TAVS, we also present a strong multi-modal video segmentation baseline coupled with multi-label class prediction. Extensive experiments are conducted to evaluate our proposed method as well as existing representative methods to reveal key challenges of our dataset TAVS

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

Current Resources

Reviews include: Family Centered Services: A Handbook for Practitioners.Bonnie K. Williams (Ed.). The National Resource Center for Family Centered Practice, School of Social Work, The University of Iowa. Iowa City, Iowa.Reviewed by Lois Wright Building Skills in High-Risk Families: Strategies for the Home-Based Practitioner. Jane Peterson, Paula E. Kohrt, Linda M. Shadoin, Karen J. Authier. Boys Town, Nebraska. Boys Town Press. Reviewed by Sharon Alper

Changes in lifeguards’ hazard detection and eye movements with experience: is one season enough?

Surveillance is key to the lifesaving capability of lifeguards. Experienced personnel consistently display enhanced hazard detection capabilities compared to less experienced counterparts. However, the mechanisms which underpin this effect and the time it takes to develop these skills are not understood. We hypothesized that, after one season of experience, the number of hazards detected by, and eye movements of, less experienced lifeguards (LEL) would more closely approximate experienced lifeguards (EL). The LEL watched ‘beach scene’ videos at the beginning and end of their first season. The number of hazards detected and eye-movement data were collected and compared to the EL group. The LEL perceived fewer hazards than EL and did not increase over the season. There was no difference in eye-movements between groups. Findings suggest one season is not enough for lifeguards to develop enhanced hazard detection skills and skill level differences are not underpinned by differences in gaze behavior

Changes in Lifeguards’ Hazard Detection and Eye Movements with Experience: Is One Season Enough?

Surveillance is key to the lifesaving capability of lifeguards. Experienced personnel consistently display enhanced hazard detection capabilities compared to less experienced counterparts. However, the mechanisms which underpin this effect and the time it takes to develop these skills are not understood. We hypothesized that, after one season of experience, the number of hazards detected by, and eye movements of, less experienced lifeguards (LEL) would more closely approximate experienced lifeguards (EL). The LEL watched ‘beach scene’ videos at the beginning and end of their first season. The number of hazards detected and eye-movement data were collected and compared to the EL group. The LEL perceived fewer hazards than EL and did not increase over the season. There was no difference in eye-movements between groups. Findings suggest one season is not enough for lifeguards to develop enhanced hazard detection skills and skill level differences are not underpinned by differences in gaze behavior

"You Tube and I Find" - personalizing multimedia content access

Recent growth in broadband access and proliferation of small personal devices that capture images and videos has led to explosive growth of multimedia content available everywhereVfrom personal disks to the Web. While digital media capture and upload has become nearly universal with newer device technology, there is still a need for better tools and technologies to search large collections of multimedia data and to find and deliver the right content to a user according to her current needs and preferences. A renewed focus on the subjective dimension in the multimedia lifecycle, fromcreation, distribution, to delivery and consumption, is required to address this need beyond what is feasible today. Integration of the subjective aspects of the media itselfVits affective, perceptual, and physiological potential (both intended and achieved), together with those of the users themselves will allow for personalizing the content access, beyond today’s facility. This integration, transforming the traditional multimedia information retrieval (MIR) indexes to more effectively answer specific user needs, will allow a richer degree of personalization predicated on user intention and mode of interaction, relationship to the producer, content of the media, and their history and lifestyle. In this paper, we identify the challenges in achieving this integration, current approaches to interpreting content creation processes, to user modelling and profiling, and to personalized content selection, and we detail future directions. The structure of the paper is as follows: In Section I, we introduce the problem and present some definitions. In Section II, we present a review of the aspects of personalized content and current approaches for the same. Section III discusses the problem of obtaining metadata that is required for personalized media creation and present eMediate as a case study of an integrated media capture environment. Section IV presents the MAGIC system as a case study of capturing effective descriptive data and putting users first in distributed learning delivery. The aspects of modelling the user are presented as a case study in using user’s personality as a way to personalize summaries in Section V. Finally, Section VI concludes the paper with a discussion on the emerging challenges and the open problems

Smart augmented reality instructional system for mechanical assembly

Quality and efficiency are pivotal indicators of a manufacturing company. Many companies are suffering from shortage of experienced workers across the production line to perform complex assembly tasks such as assembly of an aircraft engine. This could lead to a significant financial loss. In order to further reduce time and error in an assembly, a smart system consisting of multi-modal Augmented Reality (AR) instructions with the support of a deep learning network for tool detection is introduced. The multi-modal smart AR is designed to provide on-site information including various visual renderings with a fine-tuned Region-based Convolutional Neural Network, which is trained on a synthetic tool dataset. The dataset is generated using CAD models of tools augmented onto a 2D scene without the need of manually preparing real tool images. By implementing the system to mechanical assembly of a CNC carving machine, the result has shown that the system is not only able to correctly classify and localize the physical tools but also enables workers to successfully complete the given assembly tasks. With the proposed approaches, an efficiently customizable smart AR instructional system capable of sensing, characterizing the requirements, and enhancing worker\u27s performance effectively has been built and demonstrated --Abstract, page iii