Activities in extended video

In this paper, we present a system based on detection, tracking and 3D convolution neural network dealing with Activities in Extended Video (ActEV) task in TRECVID 2018. In the proposed system, videos are first unfolded into frames for training detection network, then we use it to generate bounding box for tracking areas where target activities could be happen. The tracking clips are then classified using a 3D convulution network

Digitized Local Folklores in EFL Reading Classroom

This study aimed at reporting the implementation of the use of digitized local folklores to empower reading comprehension skills of junior high school students. This classroom action study was applied to a number of grade VII junior high school students. It engaged two stories about Palembang City - the Origin of Musi River and the History of Ikan Belido (Chitala Lopis). Both stories were “packaged” digitally by the use of video, and extended with guided ICT based post-reading activities. Video as one medium of the learning activities could confidently intensify students’ interest in learning due to the fact that most students tend to be more visualized. The result revealed that the use of this digitized media positively enhanced the students on the extent of the pleasure, imaginative visual learning aids, and the involvement and touched upon cultural aspects of the students

Industrial Human Activity Prediction and Detection Using Sequential Memory Networks

Prediction of human activity and detection of subsequent actions is crucial for improving the interaction between humans and robots during collaborative operations. Deep-learning techniques are being applied to recognize human activities, including industrial applications. However, the lack of sufficient dataset in the industrial domain and complexities of some industrial activities such as screw driving, assembling small parts, and others affect the model development and testing of human activities. The InHard dataset (Industrial Human Activity Recognition Dataset) was recently published to facilitate industrial human activity recognition for better human-robot collaboration, which still lacks extended evaluation. We propose an activity recognition method using a combined convolutional neural network (CNN) and long short-term memory (LSTM) techniques to evaluate the InHard dataset and compare it with a new dataset captured in a lab environment. This method improves the success rate of activity recognition by processing temporal and spatial information. Accordingly, the accuracy of the dataset is tested using labeled lists of activities from IMU and video data. A model is trained and tested for nine low-level activity classes with approximately 400 samples per class. The test result shows 88% accuracy for IMU-based skeleton data, 77% for RGB spatial video, and 63% for RGB video-based skeleton. The result has been verified using a previously published region-based activity recognition. The proposed approach can be extended to push the cognition capability of robots in human-centric workplaces

Observational Outcome Measures to Evaluate Assistive Technology Use by People with Dementia - Report Series # 12

This report describes a digital video-audio behavioural observation methodology for use in a naturalistic setting to evaluate communication rehabilitation interventions for older adults with dementia. Behavioural observation via recorded video-audio offers a number of advantages over other data collection methodologies, which can be subject to a number of biases and limitations, some of which are discussed. In this study, high quality digital audio-video recordings were collected on participants attending a respite care day program. Recording equipment was inconspicuously placed, and measurement occurred either during normal day-to-day activities or during more directed activities (e.g., playing bingo). The recordings can be used to document the occurrence of behaviours and paired behaviours of interest over extended periods of time or selected samples of interest can be downloaded for detailed analysis including lag-sequential analyses. It was found that behavioural observation can complement traditional objective measures of impairment and subjective questionnaire measures, in accordance with the World Health Organization’s (WHO) International Classification of Functioning, Disability, and Health (2001)

Human Activity Recognition Based on R Transform

This paper addresses human activity recognition based on a new feature descriptor. For a binary human silhouette, an extended radon transform, transform, is employed to represent low-level features. The advantage of the trans-form lies in its low computational complexity and geomet-ric invariance. Then a set of HMMs based on the extracted features are trained to recognize activities. Compared with other commonly-used feature descriptors, transform is robust to frame loss in video, disjoint silhouettes and holes in the shape, and thus achieves better performance in rec-ognizing similar activities. Rich experiments have proved the efficiency of the proposed method. 1

Active Learning on Center Stage: Theater as a Tool for Medical Education

Introduction: Knowledge and skill development related to communication must incorporate both affective and behavioral components, which are often difficult to deliver in a learning activity. Using theater techniques and principles can provide medical educators with tools to teach communication concepts. Methods: This 75-minute faculty development workshop presents a variety of techniques from theater and adapts them for use in medical education. Using examples related to diversity and inclusion, this session addresses general educational and theater principles, role-play, sociodrama, applied improvisation, and practical aspects of involving theater partners. The session materials include a PowerPoint presentation with facilitator notes, interactive activities to demonstrate each modality, and an evaluation. The sessions can be extended to longer formats as needed. Results: Forty-five participants at Learn Serve Lead 2016: The AAMC Annual Meeting attended the 75-minute session. We emailed 32 participants 5 months after the conference, and eight responded. Participants reported that their confidence level in using theater techniques as a tool for medical education increased from low-to-medium confidence presession to high confidence postsession. All survey respondents who were actively teaching said they had made changes to their teaching based on the workshop. All commented that they appreciated the active learning in the session. Many indicated they would appreciate video or other follow-up resources. Discussion: Principles and techniques from theater are effective tools to convey difficult-to-teach concepts related to communication. This workshop presents tools to implement activities in teaching these difficult concepts