TY  - CONF
AU  - Zhijie Fang
AU  - Antonio Lopez
A2  - IV
PY  - 2018//
TI  - Is the Pedestrian going to Cross? Answering by 2D Pose Estimation
BT  - IEEE Intelligent Vehicles Symposium
SP  - 1271
EP  - 1276
N2  - Our recent work suggests that, thanks to nowadays powerful CNNs, image-based 2D pose estimation is a promising cue for determining pedestrian intentions such as crossing the road in the path of the ego-vehicle, stopping before entering the road, and starting to walk or bending towards the road. This statement is based on the results obtained on non-naturalistic sequences (Daimler dataset), i.e. in sequences choreographed specifically for performing the study. Fortunately, a new publicly available dataset (JAAD) has appeared recently to allow developing methods for detecting pedestrian intentions in naturalistic driving conditions; more specifically, for addressing the relevant question is the pedestrian going to cross? Accordingly, in this paper we use JAAD to assess the usefulness of 2D pose estimation for answering such a question. We combine CNN-based pedestrian detection, tracking and pose estimation to predict the crossing action from monocular images. Overall, the proposed pipeline provides new state-ofthe-art results.
UR  - https://ieeexplore.ieee.org/abstract/document/8500413
L1  - http://refbase.cvc.uab.es/files/FaL2018.pdf
UR  - http://dx.doi.org/10.1109/IVS.2018.8500413
N1  - ADAS; 600.124; 600.116; 600.118
ID  - Zhijie Fang2018
ER  -