Joceyln Chan
Papers
1
Total Citations
6
H-Index
1
About
Dr. Jocelyn Chan is a leading researcher in the field of 3D computer vision, with a particular focus on stereo vision systems for robotics. Her most cited work, "Optimization-based automatic parameter tuning for stereo vision" (2015), addresses a critical bottleneck in deploying stereo cameras for real-world applications: the labor-intensive manual calibration required to achieve high-quality depth maps. By developing an automatic, optimization-driven method for parameter tuning, Chan’s research significantly reduces the setup time and expertise needed to leverage the inherent advantages of stereo vision—such as high depth resolution, low cost, and low power consumption—over active sensors like LiDAR. This contribution is foundational for making dense 3D sensing more accessible for robotic navigation and manipulation. With 6 citations on her seminal paper, Chan’s work is gaining traction among engineers seeking practical, efficient solutions for autonomous systems. Her research directly supports the goal of creating smaller, cheaper, and more energy-efficient perception modules, positioning her as a key innovator in the push toward robust, passively-sensed 3D environments for next-generation robotics.
Research Focus
Key Achievements
Top Papers
- 1Optimization-based automatic parameter tuning for stereo vision6 citations · 2015