@inproceedings{b1283cb0147a4ff3867d753f3f95c131,
title = "DD-Pose: A large-scale Driver Head Pose Benchmark",
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.",
author = "Markus Roth and Dariu Gavrila",
note = "Accepted Author Manuscript; IEEE Intelligent Vehicles Symposium 2019 , IV 2019 ; Conference date: 09-06-2019 Through 12-06-2019",
year = "2019",
doi = "10.1109/IVS.2019.8814103",
language = "English",
isbn = "978-1-7281-0560-4",
pages = "927--934",
booktitle = "Proceedings IEEE Symposium Intelligent Vehicles (IV 2019)",
publisher = "IEEE",
address = "United States",
}