Mubashir Javaid¹, Muazzam Maqsood², Farhan Aadil², Jibran Safdar¹, Yongsung Kim^3,*

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1295-1310, 2023, DOI:10.32604/iasc.2023.028262

Abstract Currently, worldwide industries and communities are concerned with building, expanding, and exploring the assets and resources found in the oceans and seas. More precisely, to analyze a stock, archaeology, and surveillance, several cameras are installed underseas to collect videos. However, on the other hand, these large size videos require a lot of time and memory for their processing to extract relevant information. Hence, to automate this manual procedure of video assessment, an accurate and efficient automated system is a greater necessity. From this perspective, we intend to present a complete framework solution for the task of video summarization and object… More >

Hilal Ahmad¹, Habib Ullah Khan², Sikandar Ali^3,*, Syed Ijaz Ur Rahman¹, Fazli Wahid³, Hizbullah Khattak⁴

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1427-1442, 2022, DOI:10.32604/cmc.2022.021158

Abstract Video summarization is applied to reduce redundancy and develop a concise representation of key frames in the video, more recently, video summaries have been used through visual attention modeling. In these schemes, the frames that stand out visually are extracted as key frames based on human attention modeling theories. The schemes for modeling visual attention have proven to be effective for video summaries. Nevertheless, the high cost of computing in such techniques restricts their usability in everyday situations. In this context, we propose a method based on KFE (key frame extraction) technique, which is recommended based on an efficient and… More >