DD-Pose
A large-scale Driver Head Pose Benchmark
Markus Roth (TU Delft - Mechanical Engineering, Daimler AG)
Dariu Gavrila (TU Delft - Mechanical Engineering)
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Abstract
We introduce DD-Pose, the Daimler TU Delft Driver Head Pose Benchmark, a large-scale and diverse benchmark for image-based head pose estimation and driver analysis. It contains 330k measurements from multiple cameras acquired by an in-car setup during naturalistic drives. Large out-of-plane head rotations and occlusions are induced by complex driving scenarios, such as parking and driver-pedestrian interactions. Precise head pose annotations are obtained by a motion capture sensor and a novel calibration device. A high resolution stereo driver camera is supplemented by a camera capturing the driver cabin. Together with steering wheel and vehicle motion information, DD-Pose paves the way for holistic driver analysis. Our experiments show that the new dataset offers a broad distribution of head poses, comprising an order of magnitude more samples of rare poses than a comparable dataset. By an analysis of a state-of-the-art head pose estimation method, we demonstrate the challenges offered by the benchmark. The dataset and evaluation code are made freely available to academic and non-profit institutions for non-commercial benchmarking purposes.