Saud S. Alotaibi

Papers

Total Citations

102

H-Index

About

Saud S. Alotaibi is a prominent researcher specializing in computer vision, human-computer interaction, and intelligent surveillance systems, with a particular focus on applying deep learning and machine learning techniques to understand and interpret human behavior. His work spans several interconnected domains, including human action recognition, gesture recognition, and human interaction analysis, addressing real-world challenges in surveillance, social robotics, and assistive technology. Among his most impactful contributions is his 2023 investigation into aerial human action recognition using deep learning applied to drone imagery, which has garnered an impressive 62 citations, reflecting its significance in advancing autonomous monitoring systems. Equally noteworthy is his research developing a novel human interaction framework combining Quadratic Discriminant Analysis with Hidden Markov Models, demonstrating his versatility across both statistical and deep learning approaches. His work on hand gesture recognition for character understanding holds particular humanitarian value, targeting communication barriers faced by the deaf community through convex hull landmarks and geometric features. Collectively, Alotaibi's research addresses some of the most pressing challenges at the intersection of artificial intelligence and human behavior understanding, making meaningful contributions to accessible technology, public safety, and intelligent systems design.