DD-Pose: A large-scale Driver Head Pose Benchmark

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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.
Original languageEnglish
Title of host publicationProceedings IEEE Symposium Intelligent Vehicles (IV 2019)
Place of PublicationPiscataway, NJ, USA
ISBN (Electronic)978-1-7281-0560-4
ISBN (Print)978-1-7281-0560-4
Publication statusPublished - 2019
EventIEEE Intelligent Vehicles Symposium 2019 - Paris, France
Duration: 9 Jun 201912 Jun 2019


ConferenceIEEE Intelligent Vehicles Symposium 2019
Abbreviated titleIV 2019

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