Yilin Chen
Papers
1
Total Citations
16
H-Index
1
About
Yilin Chen is a researcher whose work centers on 3D spatial data processing, with a particular focus on point cloud compression and streaming technologies. Their most notable contribution is the development of a dynamic compression technique for streaming Kinect-based point cloud data, published in 2017 and cited 16 times. This work addresses a critical bottleneck in the practical deployment of 3D sensors: the massive data rates generated by these devices. By enabling efficient compression without sacrificing quality, Chen’s research has opened new possibilities for real-time applications in robotics, telemedicine, and entertainment, where low-latency 3D data transmission is essential. The study highlights the growing accessibility of 3D sensors and the corresponding need for scalable data handling solutions. Chen’s work is particularly impactful for students and researchers exploring the intersection of computer vision, data compression, and human-computer interaction, offering a foundational approach to making point cloud data more practical for real-world systems.
Research Focus
Key Achievements
Top Papers
- 1A dynamic compression technique for streaming kinect-based Point Cloud data16 citations · 2017