摘要: |
The goal of this project is to develop a comprehensive automatic coding system: DCode. The code will pay attention to the context of various driving situations by extracting features related to driver behavior as well as to features related to the environment both inside and outside of the vehicle. The overall algorithm will include a multitiered feature-extraction pipeline with a behavior-agnostic core layer and more behavior-specific upper layers that share features with the core layer. The core layer will track all directly observable features, such as head pose, facial features, upper body, and hand positions, as well as pedestrian and vehicle locations. The upper layers will use these features to identify various actions and gestures, as well as monitor the driver’s state based on various machine-learning techniques. This architecture will make it straightforward to add new behavior detectors. The algorithms will be scalable, so they can be run on distributed processor architectures. |