単眼動画からの自動車衝突リスクのリアルタイム予測
Real-time Prediction of Automotive Collision Risk from Monocular Video
ダッシュボードカメラの単眼動画から物体検出・追跡・状態推定を行い、10秒先までの衝突リスクを5Hz以上でリアルタイム予測する低コストシステムを提案した。
著者: Derek J. Phillips, Juan Carlos Aragon, Anjali Roychowdhury, Regina Madigan, Sunil Chintakindi, Mykel J. Kochenderfer
分類: cs.CV, cs.RO
原文アブストラクト
Many automotive applications, such as Advanced Driver Assistance Systems (ADAS) for collision avoidance and warnings, require estimating the future automotive risk of a driving scene. We present a low-cost system that predicts the collision risk over an intermediate time horizon from a monocular video source, such as a dashboard-mounted camera. The modular system includes components for object detection, object tracking, and state estimation. We introduce solutions to the object tracking and distance estimation problems. Advanced approaches to the other tasks are used to produce real-time predictions of the automotive risk for the next 10 s at over 5 Hz. The system is designed such that alternative components can be substituted with minimal effort. It is demonstrated on common physical hardware, specifically an off-the-shelf gaming laptop and a webcam. We extend the framework to support absolute speed estimation and more advanced risk estimation techniques.
