Viet Vo

About

Dr. Viet Vo is a researcher in computer vision whose work focuses on the challenging problem of human action and activity recognition from video sequences. His research addresses core difficulties in the field, such as variations in illumination, background clutter, occlusion, and subtle behavioral patterns. Dr. Vo has made notable contributions by developing effective feature extraction and representation methods. His most cited work, "An effective approach for human actions recognition based on optical flow and edge features" (2012, 8 citations), proposes a novel method for deriving action representations by combining optical flow and edge information. He further advanced the field by exploring the fusion of multiple modal features with multiple kernel learning for daily activity recognition (2018, 5 citations), and by improving the Bag-of-Words model with hybrid features for robust action recognition (2012, 3 citations). Dr. Vo’s research has significant implications for applications in human-computer interaction, intelligent surveillance, and robotics, demonstrating a sustained commitment to solving one of computer vision's most complex and impactful problems.

Research Focus

Key Achievements

Top Papers

1. 1
   An effective approach for human actions recognition based on optical flow and edge features

   8 citations · 2012
2. 2
   Multiple Modal Features and Multiple Kernel Learning for Human Daily Activity Recognition

   5 citations · 2018
3. 3
   Robust human action recognition using improved BOW and hybrid features

   3 citations · 2012

Key Collaborators

Contact & Links