Deep attentive video summarization with distribution consistency learning

This article studies supervised video summarization by formulating it into a sequence-to-sequence learning framework, in which the input and output are sequences of original video frames and their predicted importance scores, respectively. Two critical issues are addressed in this article: short-term contextual attention insufficiency and distribution inconsistency. The former lies in the insufficiency of capturing the short-term contextual attention information within the video sequence itself since the existing approaches focus a lot on the long-term encoder-decoder attention. The latter refers to the distributions of predicted importance score sequence and the ground-truth sequence is inconsistent, which may lead to a suboptimal solution. To better mitigate the first issue, we incorporate a self-attention mechanism in the encoder to highlight the important keyframes in a short-term context. The proposed approach alongside the encoder-decoder attention constitutes our deep attentive models for video summarization. For the second one, we propose a distribution consistency learning method by employing a simple yet effective regularization loss term, which seeks a consistent distribution for the two sequences. Our final approach is dubbed as Attentive and Distribution consistent video Summarization (ADSum). Extensive experiments on benchmark data sets demonstrate the superiority of the proposed ADSum approach against state-of-the-art approaches

Development of Video Learning Media Based on Powtoon Application on the Concept of the Properties of Light for Elementary School Students

The purpose of this research is to know the process of development and feasibility of the learning media of Powtoon and analyze student\u27s understanding after using media in the learning. This research is research and development, the models of construction adopted by Borg and Gall. The product is tested for eligibility through validation testing by the content and media experts. The subject of this study was a student of class IV SDN 3 Attack as much as 20 students. Based on the analysis of the data acquired that a learning-based media of Powtoon is declared feasible by the media experts with an average percentage score of 88% and content expert with a percentage of 80%. the response of students with a rate of 98% the which included "excellent," as well as test of student\u27s understanding, gained an average of scores of 89.25, which belongs to the category of "excellent." From the study, it can to be concluded that learning deserves media of powtoon use in the learning process on the property of light topic

Video Styles and Learning

With the current prevalence of online and distance learning, videos are becoming a larger part of our education system. It is important that we be able to fully utilize the potential of videos as education tools. Videos make use of more senses than just printed materials, and provide greater flexibility for both teachers and students (Bevan). What qualities make a good educational video? We believe that to be effective at teaching a video needs to be interesting enough to students’ attention and have enough information to be useful. By surveying a number of college students, we were able to support my hypothesis. With this information, we will be able to better select and create instructional videos both in academia and in the world at large

Video analysis : A qualitative tool for investigating students' learning in a constructivist-oriented multimedia in a science classroom

A new software package VideoSearch, a Macintosh multimedia research tool for analysing digital video was used to analyse classroom observations. VideoSearch can digitise video from a video cassette recorder or video camera and store it on a computer as a QuickTime movie. Texts can be attached to each instance within an episode and this text can be searched. Episodes in this movie can then be coded for analysis by means of user defined categories. Analyses of three types of episodes from video segments are presented and discussed in order to investigate students' learning. Episodes from video segments include students working in pairs conducting investigations based on an inquiry- based multimedia program, students presenting their experiences of their process of investigation and the researcher probing the students' reflections on their learning during an interview. An advantage of working with the digital video analysis is greater access to fuller context for qualitative data analyses. This allows for a better understanding of the social processes of students' learning. However, the time required and the level of intensive analysis may make it a difficult process to undertake

Leveraging video annotations in video-based e-learning

The e-learning community has been producing and using video content for a long time, and in the last years, the advent of MOOCs greatly relied on video recordings of teacher courses. Video annotations are information pieces that can be anchored in the temporality of the video so as to sustain various processes ranging from active reading to rich media editing. In this position paper we study how video annotations can be used in an e-learning context - especially MOOCs - from the triple point of view of pedagogical processes, current technical platforms functionalities, and current challenges. Our analysis is that there is still plenty of room for leveraging video annotations in MOOCs beyond simple active reading, namely live annotation, performance annotation and annotation for assignment; and that new developments are needed to accompany this evolution.Comment: 7th International Conference on Computer Supported Education (CSEDU), Barcelone : Spain (2014

Towards developing a collaborative video platform for learning

The work presented in this paper outlines issues relating to the development of a collaborative video platform for learning. Student adoption of collaborative and video technology is increasing dramatically, becoming part of their everyday lives. The aim of this paper is to propose a system and framework for the successful integration of these technologies into teaching and learning. At the outset we assess current trends and previous research, using these findings to inform the development of a new platform. System specifications are then presented with specific needs identified for students and educators. Finally our tentative framework for a integrating a collaborative video platform for learning is presented

EFFECTIVENESS OF USING VIDEO IN THE LEARNING OF COMPUTER HARDWARE ASSEMBLING CLASS XII INDUSTRIAL ELECTRONICS IN SMK NEGERI 2 WONOSARI

This study aims to determine the effectiveness of video in the learning materials and computer hardware assembling to know the difference student learning outcomes before and after using video in class XII Industrial Electronics SMKN 2 Wonosari. This research was conducted in November 2010 until December 2010. Type research is kind of population research because the sample size research take the entire population of the entire class XII students of Industrial Electronics, this population is 35 students. Research’s method is Pre-Experimental Designs and using One-Group Pretest-Posttest Design. This method aims to determine the effect of a treatment in the learning process. The media used is a CD video tutorial "Merakit Komputer Untuk Orang Awam." Data collection techniques used in this research using a pretest and posttest. Validation of research instruments is through expert opinions (judgments) and then tested through a pretest on students majoring in Industrial Electronics XII SMK N 2 Wonosari. Data analysis techniques used to analyze the research data is to be tested in SPSS 17 for Windows. Based on a research known to increase learning outcomes after a given treatment using video CD Tutorial is from 63.97 (mean pretest) to 76.37 (mean posttest). Results mastery learning after using video media tutorial CD reaches 71.42% which means that these results exceeded the minimum limit of 65% so that concluded video media Tutorial CD " Merakit Komputer Untuk Orang Awam " not yet effective in learning to use the lessons of computer hardware assembling class XII Industrial Electronics SMK Negeri 2 Wonosari. Keywords: effectiveness, video, computer hardware assembling

Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization

In this paper, we present a novel unsupervised video summarization model that requires no manual annotation. The proposed model termed Cycle-SUM adopts a new cycle-consistent adversarial LSTM architecture that can effectively maximize the information preserving and compactness of the summary video. It consists of a frame selector and a cycle-consistent learning based evaluator. The selector is a bi-direction LSTM network that learns video representations that embed the long-range relationships among video frames. The evaluator defines a learnable information preserving metric between original video and summary video and "supervises" the selector to identify the most informative frames to form the summary video. In particular, the evaluator is composed of two generative adversarial networks (GANs), in which the forward GAN is learned to reconstruct original video from summary video while the backward GAN learns to invert the processing. The consistency between the output of such cycle learning is adopted as the information preserving metric for video summarization. We demonstrate the close relation between mutual information maximization and such cycle learning procedure. Experiments on two video summarization benchmark datasets validate the state-of-the-art performance and superiority of the Cycle-SUM model over previous baselines.Comment: Accepted at AAAI 201