Proceedings ArticleDOI
Are They Going to Cross? A Benchmark Dataset and Baseline for Pedestrian Crosswalk Behavior
Amir Rasouli,Iuliia Kotseruba,John K. Tsotsos +2 more
- pp 206-213
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TLDR
A novel dataset is introduced which in addition to providing the bounding box information for pedestrian detection, also includes the behavioral and contextual annotations for the scenes, which allows combining visual and semantic information for better understanding of pedestrians' intentions in various traffic scenarios.Abstract:
Designing autonomous vehicles suitable for urban environments remains an unresolved problem. One of the major dilemmas faced by autonomous cars is how to understand the intention of other road users and communicate with them. The existing datasets do not provide the necessary means for such higher level analysis of traffic scenes. With this in mind, we introduce a novel dataset which in addition to providing the bounding box information for pedestrian detection, also includes the behavioral and contextual annotations for the scenes. This allows combining visual and semantic information for better understanding of pedestrians' intentions in various traffic scenarios. We establish baseline approaches for analyzing the data and show that combining visual and contextual information can improve prediction of pedestrian intention at the point of crossing by at least 20%.read more
Citations
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Proceedings ArticleDOI
Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion
TL;DR: TransML as discussed by the authors is a pedestrian stop-and-go dataset, which is built from several existing datasets annotated with pedestrians' walking motions, in order to have various scenarios and behaviors.
Patent
Method of pedestrian activity recognition using limited data and meta-learning
Saleem Muneeb,Nikhil George +1 more
TL;DR: In this paper, a Siamese neural network is trained to recognize a plurality of pedestrian activities by training it recordings of the same pedestrian activity from two or more separate training image capture devices.
Journal ArticleDOI
DeepStep: Direct Detection of Walking Pedestrian From Motion by a Vehicle Camera
TL;DR: Zhang et al. as mentioned in this paper proposed a deep learning-based pedestrian detection method that only uses motion cues, where the pedestrian leg movement forms a chain-type trace in the motion profile images even if the ego-vehicle moves.
Journal ArticleDOI
Pedestrian Behavior and Interaction with Autonomous Vehicles
Saki Rezwana,Nicholas E Lownes +1 more
Journal ArticleDOI
STAF: Spatio-Temporal Attention Framework for Understanding Road Agents Behaviors
TL;DR: This paper proposes a new approach called STAF (Spatio- Temporal Attention Framework) through Long Short Term Memory (LSTM) layers that uses a multi-head attention mechanism on its past cell state to focus on attributes that are relevant over time.
References
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