The system identifies keywords and links them to the corresponding Wikipedia links without any manual intervention. Secondly, AutoNotes reduces the reference search time for learners by eliminating the requirement of manually marking keywords or searching them in Web. The contact-free interface makes it ideal for the current pandemic situation. The contributions of the paper are as follows: Firstly, the paper depicts a novel interactive yet contact-free video control system that utilizes user’s blink counts for selection of lecture segments and automatic generation of textual notes and diagrams from these sections. A video instance can also be paused, captured or closed by blinks or gazing down. This is followed by a speech to text translation, keyword retrieval and generation of Wikipedia links for the keywords. The model is an integration of simultaneous eye tracking from the user’s preview, notes selection and image capture based on the blink counts. In this paper, a novel, automated note-generation system has been proposed which can be controlled through simple blinks.
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However, such a model needs to address generic problems like the free head movement, context switching and restricted set of gestures to be used for controlling the interface. Since the process of taking notes for relevant article search is essential, the mentioned intricacies necessitate an interface that does not require physical contact like button clicks and can be controlled through facial cues for selecting the sections from the lecture and generate relevant links for the keywords. This is further infeasible if the course is being followed by the learner in a mobile scenario.
While key terms can be noted quickly, noting down figures or descriptions while the online video is being played, requires repetitive pausing and playing involving physical contact with the device. These may include keywords or figures shown in a video. The learner might often look into important terms discussed in a lecture and find relevant materials from other online resources. In the case of confusion, the learner often takes note of the important points so that the queries can be mediated later. Even in a real-time presentation, it is often impractical to discuss each of the personal queries. However, in pre-recorded video lectures, the pace of delivery of the contents does not match with that of cognition for every student. The inflation in the utility of online courses is also a direct result of this scenario. Moreover, the unforeseen pandemic situation due to the COVID-19 virus has led to the avoidance of mass gathering and limiting physical contact among individuals and devices. Massive Online Courses (MOOCs) have gained enormous popularity due to the evolution of traditional learning from centralized classrooms to global knowledge distribution. The experimental results reveal 84.17 usability score, an average of 89.55% of different types of blink detection accuracy, 91.56% of text generation accuracy and 70.41% of keyword detection accuracy along with low false positives and false negatives under different lighting conditions.
Functions like auto-video pausing and auto-closing of the application based on eye attribute tracking have been integrated into the system for handling context switching. The proposed model introduces a novel approach that facilitates the automated generation of relevant lecture notes and web-linked keywords from videos through a blink-controlled interface. Visual gestures like simple blinks can account for a significant subset of possible actions in mobile application domains. While the enforced social distancing protocol inevitably demands the involvement of technology in raising awareness, it further requires the imposition of preventive restrictions on touch-based systems.
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The recent explosion of interest in online courses can directly be attributed to the current pandemic which has collated to the adoption of Massive Open Online Courses.
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