ABSTRACT:--
Now day‘s users are interested in distance learning as there is rapid growth in digital data due to day today development in information as well as computer technology. Also, its applications or usage have a tremendous response in the market. Peoples are attracted towards interactivity in each thing, we found that for e-learning is a very interactive way to learn and understand things. Currently, YouTube is the global way of video sharing. It is having certain limitations such as it having inactivity in online learning. In online study students expecting some extra guidelines from given resources. In this project, we developed video annotation system for foster active learning. In this project, we achieved active participation of students. There is certain kind of technologies that extract some important keywords from textual information. MOOC‘s model is another technology to solve interaction problem of users in active learning. It also has limitations that it suffered from the problem of gamification. Our system is interactive as it provides real-time annotations to the video. In our system user can give their active participation as they have direct interaction to our system. As part of our contribution in this project, we did SVM analysis to provide recommended videos for end users. SVM is Support Vector Machine algorithm; it classifies the things according to user interest. So, in our system user can search for video and they get recommended video list for their study.
Keywords: Feature extraction, Video Annotation, Retrieval, E-Learning, Workplace Training, Tagging, and Classification.
INTRODUCTION:--
According to a survey of distance learning in educational development. In 2011, U.S country students are applying for at least one online course in a semester. For distance learning there is virtual environment is created as there is physical distance between students and lecturer in distance learning. As everyone know that, today YouTube act as a central hub for sharing online video. But it is invaluable tool for professional learning. For professional learning there is need of such tool that make learning session interactive, informative and make people engaged. In short, a tool that has capability of transferring boring as well as difficult lectures into an interactive and exciting learning experience. One approach is known as teleteaching approach.
It is collaborative video annotation strategy in the digital world. It required to collect culture participations to improve active learning. We developed a system called as video annotation system. It supports interactive learning as well as to share large amount of metadata in short time period. Certain technologies like OCR and ASR are used to extract important keywords from textual line given in video. But it seems not much efficient for video annotation. Our system provides real-time annotation for running video. In our system user can mark or annotate important points from running video. MOOC model is “Massive Open Online Course”. It mainly used to solve human interaction problems in virtual scalable laboratories. MOOCS model used in e-learning to support all services of it i.e. interacting with learners in that environment. It is helpful to make students engaged in lectures that are conducted online. In our system, students can create a group as they have their own accounts on social networks. students can have discussion on video lectures.
Our research analyze that there is need of such system that can deal with both individual and group annotations. Also there is need of such manuscript that allows students to have some searchable notes with a timestamp that enables them to jump into the video at the desired points for revision. Also the learning effectiveness when watching e-lectures showed a tendency to be higher when students used the manuscript function in addition to watching the video. The main focus of our research is to present identification of digital video annotation that provides added benefits and to make
Now day‘s users are interested in distance learning as there is rapid growth in digital data due to day today development in information as well as computer technology. Also, its applications or usage have a tremendous response in the market. Peoples are attracted towards interactivity in each thing, we found that for e-learning is a very interactive way to learn and understand things. Currently, YouTube is the global way of video sharing. It is having certain limitations such as it having inactivity in online learning. In online study students expecting some extra guidelines from given resources. In this project, we developed video annotation system for foster active learning. In this project, we achieved active participation of students. There is certain kind of technologies that extract some important keywords from textual information. MOOC‘s model is another technology to solve interaction problem of users in active learning. It also has limitations that it suffered from the problem of gamification. Our system is interactive as it provides real-time annotations to the video. In our system user can give their active participation as they have direct interaction to our system. As part of our contribution in this project, we did SVM analysis to provide recommended videos for end users. SVM is Support Vector Machine algorithm; it classifies the things according to user interest. So, in our system user can search for video and they get recommended video list for their study.
Keywords: Feature extraction, Video Annotation, Retrieval, E-Learning, Workplace Training, Tagging, and Classification.
INTRODUCTION:--
According to a survey of distance learning in educational development. In 2011, U.S country students are applying for at least one online course in a semester. For distance learning there is virtual environment is created as there is physical distance between students and lecturer in distance learning. As everyone know that, today YouTube act as a central hub for sharing online video. But it is invaluable tool for professional learning. For professional learning there is need of such tool that make learning session interactive, informative and make people engaged. In short, a tool that has capability of transferring boring as well as difficult lectures into an interactive and exciting learning experience. One approach is known as teleteaching approach.
It is collaborative video annotation strategy in the digital world. It required to collect culture participations to improve active learning. We developed a system called as video annotation system. It supports interactive learning as well as to share large amount of metadata in short time period. Certain technologies like OCR and ASR are used to extract important keywords from textual line given in video. But it seems not much efficient for video annotation. Our system provides real-time annotation for running video. In our system user can mark or annotate important points from running video. MOOC model is “Massive Open Online Course”. It mainly used to solve human interaction problems in virtual scalable laboratories. MOOCS model used in e-learning to support all services of it i.e. interacting with learners in that environment. It is helpful to make students engaged in lectures that are conducted online. In our system, students can create a group as they have their own accounts on social networks. students can have discussion on video lectures.
Our research analyze that there is need of such system that can deal with both individual and group annotations. Also there is need of such manuscript that allows students to have some searchable notes with a timestamp that enables them to jump into the video at the desired points for revision. Also the learning effectiveness when watching e-lectures showed a tendency to be higher when students used the manuscript function in addition to watching the video. The main focus of our research is to present identification of digital video annotation that provides added benefits and to make
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