Truck and trailer classification with deep learning based geometric features

Pan He, Aotian Wu, Xiaohui Huang, Anand Rangarajan, Sanjay Ranka

Abstract:

In this paper, we present a novel and effective
approach to truck and trailer classification, which integrates deep
learning models and conventional image processing and computer
vision techniques. The developed method groups trucks into

subcategories by carefully examining the truck classes and identi-
fying key geometric features for discriminating truck and trailer

types. We also present three discriminating features that involve
shape, texture, and semantic information to identify trailer types.
Experimental results demonstrate that the developed hybrid
approach can achieve high accuracy with limited training data,
where the vanilla deep learning approaches show moderate

performance due to over-fitting and poor generalization. Addi-
tionally, the models generated are human-understandable.