Papers
1
Total Citations
7
H-Index
1
About
Wandong Xie is a researcher in computer vision and robotics, with a focus on visual tracking algorithms for autonomous systems. His most cited work, "A Scale Adaptive Mean-Shift Tracking Algorithm for Robot Vision" (2013), addresses critical limitations of the classic Mean-Shift (MS) tracker—namely, its inability to handle scale changes and occlusions in dynamic environments. Xie proposed the SAMSHIFT algorithm, which introduces adaptive scale estimation to maintain robust tracking performance even when targets vary in size or are partially hidden. This contribution has been cited 7 times and is valued for its practical applicability in robot vision, where real-time, reliable tracking is essential. Xie’s work bridges the gap between theoretical tracking methods and real-world robotic challenges, offering a computationally efficient solution that enhances the robustness of autonomous navigation and object following. His research underscores the importance of adaptive algorithms in enabling robots to interact effectively with changing environments, making his contributions relevant to both computer vision and robotics communities.
Research Focus
Key Achievements
Top Papers
- 1A Scale Adaptive Mean-Shift Tracking Algorithm for Robot Vision7 citations · 2013