Abstract
The video file is important for quickly analyzing the facts of the data or knowledge or information. To extract the specific file from the data is a time-consuming task. Managing these files is easy if they are organized in the correct format. To achieve this in video data, an indexing mechanism plays a significant role in accessing the various content in the database. Video indexing is a technique for providing an index related to video content for easy access from the frames of interest. For video indexing, machine learning and data mining approaches are used to provide better video indexing mechanisms and better searchable results for the users. Due to the huge size of the video files and the complexity involved in retrieving the video files, content-based indexing and automatic retrieval method with low human resources are proposed. Video metadata, audio data, records, and visual data are taken into account for indexing. The various machine learning concepts for video indexing are analyzed. Applications of machine learning concepts for video indexing and case studies are detailed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
