When 6D-Vision detects a moving object, the question arises whether it is a pedestrian, for whom we might not only brake but also consider a swerve maneuver in the future.
Fur this purpose, we use so-called classifiers that are trained with many pedestrian examples. This technique is applied successfully e.g. in traffic sign recognition of modern vehicles. However, traffic signs vary moderately in size and appearance whereas pedestrian recognition has many challenges:
The motion information delivered by Dense6D can even boost this performance. Currently, we are working on the answer to the question: "Will the pedestrian cross - or will he stop?" , hence we try to predict pedestrian behavior. A publication of us with this topic was recently recognized with a best paper award .
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