Year-end Sale % OFF 
Abstract
Multimedia information requires large repositories of audio-video data. Retrieval and delivery of video content is a very time-consuming process and is a great challenge for researchers. An efficient approach for faster browsing of large video collections and more efficient content indexing and access is video summarization. Compression of data through extraction of keyframes is a solution to these challenges. A keyframe is a representative frame of the salient features of the video. The output frames must represent the original video in temporal order. The proposed research presents a method of keyframe extraction using the mean of consecutive k frames of video data. A sliding window of size is employed to select the frame that matches the median entropy value of the sliding window. This is called the Median of Entropy of Mean Frames (MME) method. MME is mean-based keyframes selection using the median of the entropy of the sliding window. The method was tested for more than 500 videos of sign language gestures and showed satisfactory results.
Highlights
Gesture recognition is a giant leap toward the touch-free interface
The technique was applied to the ASL LexiconVideo Dataset, containing thousands of distinct sign classes of American Sign Language [48]
For the faster videos, we decreased the value of the k; for the slower videos, we increased the value of k
Summary
The information conveyed through gestures is either in the form of static gestures or in the form of continuous gestures [1]. The continuous gestures are represented by videos [2]. A video needs to be summarized for analysis of its content. Video summarization is used to prepare a reduced size of the video in the form of frames that can be used for indexing or content analysis. This research aims at a keyframe extraction technique that can, in turn, be used for object recognition and information retrieval. A keyframe refers to the image frame that represents the maximum information contained in a group of frames [3]. The position of the keyframe tells us about the timing of any event. The idea of keyframe usage is very powerful as it saves a great deal of processing time and requires less storage
Sign-in/Register to view highlights & summary 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 callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
