Paper Info
Title
Content-driven Multi-modal Techniques for Non-linear Video Navigation
Abstract
The growth of Massive Open Online Courses (MOOCs) has been remarkable in the last few years. A significant amount of MOOCs content is in the form of videos and participants often use non-linear navigation to browse through a video. This paper proposes the design of a system that provides non-linear navigation in educational videos using features derived from a combination of audio and visual content of a video. It provides multiple dimensions for quickly navigating to a given point of interest in a video i.e., customized dynamic time-aware word-cloud, video pages, and a 2-D timeline. In word-cloud, the relative placement of the words indicates their temporal ordering in the video whereas color codes are used to represent acoustic stress. The 2-D timeline is used to present multiple occurrences of a keyword/concept in the video in response to user click in the word-cloud. Additionally, visual content is analyzed to identify frames with \"maximum written content\", known as video pages. We conducted a user study with 20 users to evaluate the proposed system and compared it with transcription-based interfaces used by major MOOC providers. Our findings suggest that the proposed system leads to statistically significant navigation time savings especially on multimodal navigation tasks.
Year
DOI
Venue
2015
10.1145/2678025.2701408
IUI
Keywords
Field
DocType
acoustic stress,video analysis,video navigation,education,word-cloud,multimedia information systems,moocs,word cloud
Video processing,Computer science,PEVQ,Timeline,Video tracking,Smacker video,Point of interest,Video quality,Multimedia,Video compression picture types
Conference
Citations 
PageRank 
References 
12
0.75
21
Authors
7
Name
Order
Citations
PageRank
Kuldeep Yadav1809.95
Kundan Shrivastava2120.75
S. Mohana Prasad3120.75
Harish Arsikere4337.57
Sonal Patil5152.15
Ranjeet Kumar6133.81
Om Deshmukh75610.55