Real-time Street Human Motion Capture
This work addresses motion capture for applications like self-driving cars, but it appears incremental as it applies existing methods to a specific domain without clear novelty.
The paper tackles real-time human motion capture from street scene videos to generate 3D animations, applying a neural network implemented in Unity for analysis.
In recent years, motion capture technology using computers has developed rapidly. Because of its high efficiency and excellent performance, it replaces many traditional methods and is being widely used in many fields. Our project is about street scene video human motion capturing and analysis. The primary goal of the project is to capture the human motion in a video and use the motion information for 3D animation (human) in real-time. We applied a neural network for motion capture and implement it in the unity under a street view scene. By analyzing the motion data, we will have a better estimation of the street condition, which is useful for other high-tech applications such as self-driving cars.