Computer Vision and Artificial Intelligence Lab
| Principal Researcher | Jinpyung Kim |
|---|---|
| Tel | +82-31-888-9845 |
| jpkim@snu.ac.kr |
Research Areas
- This laboratory researches AI convergence technology that can be applied to the entire industry and society such as intelligent disaster safety management, smart city, drones, and autonomous driving based on various images and sensor data. To this end, we develop advanced artificial intelligence technologies: object detection, recognition, classification, position estimation in a single image and object tracking, counting, posture estimation in continuous images.
keyword
- Artificial Intelligence, Computer Vision, Image and sensor data analysis
Objective
- Deep learning-based object detection, recognition, classification, location estimation, instance segmentation technology
- Deep learning-based behavior recognition, object tracking and counting technology
- Deep learning-based posture estimation, motion estimation, and scene restoration technology
- Artificial intelligence crowd congestion estimation, vehicle location estimation, distance estimation technology using sensor data
Contents of research
- Computer Vision: This research analyzes image data collected from various visual equipment such as stereo cameras and PTZ cameras with deep learning to generate relevant information that can be applied to object detection, recognition, classification, location estimation, instance segmentation, posture estimation, and motion estimation.
- Sensor Data Analysis: This research develops related technologies such as crowd congestion estimation, vehicle location estimation, and distance estimation algorithm by connecting artificial intelligence technology with various types of sensors.
Result & Expected effect
- Computer vision, the core topic of artificial intelligence, has been successfully integrated into various industrial and social fields such as AI disaster safety management platform, smart city, drone image processing, and autonomous driving, securing original technology and spreading it to related fields.
- Contributing to the advancement of intelligent IoT sensors and the construction and application of smart AI platforms through artificial intelligence-based application analysis of various sensor data.
