Keyframe Extraction for Salient Human Activity Recognition Using a Canny Edge Detector

• Published in: SN computer science Vol. 6; no. 4; p. 380
• Main Authors: Pandey, Madhuri, Mishra, Richa, Khare, Ashish, Rathore, Vandana
• Format: Journal Article
• Language: English
• Published: Singapore Springer Nature Singapore 15.04.2025; Springer Nature B.V
• Subjects: Accuracy; Algorithms; Complexity; Computer Imaging; Computer Science; Computer Systems Organization and Communication Networks; Computing time; Data Structures and Information Theory; Datasets; Deep learning; Frames (data processing); Human activity recognition; Image processing; Information Systems and Communication Service; Literature reviews; Machine learning; Methods; Original Research; Pattern Recognition and Graphics; Research Advancements in Intelligent Computing; Sensors; Software Engineering/Programming and Operating Systems; Subject specialists; Video; Vision; Wavelet transforms; Deep learning; Canny edge detector-based; 2DCNN; Vision-based HAR; Keyframe

Technological advancements in surveillance cameras require substantial storage spaces to store human actions. Processing large video frames is complex and requires a lot of computational time to recognize human activity. This paper proposes a canny edge detector-based keyframe extraction technique f...