Symmetrical judgement area reduction and ECoHOG feature descriptor for pedestrian detection

In this study, a method to detect pedestrians using an in-vehicle camera is presented. We improved the technology in detecting pedestrians with highly accurate images using a monocular camera. We were able to predict pedestrians' activities by monitoring them, and we developed an algorithm to recognise pedestrians and their movements more accurately. For the feature descriptor, we found that an Extended Co-occurrence Histogram of Oriented Gradients (ECoHOG) was the best in decreasing both the undetectable and the excessive detectable ratio. Thus, the use of the new method by images captured on the real road was validated.