A Comparison of Neural-based Techniques Investigating Rotational Invariance for Upright People Detection in Low Resolution Imagery

Abstract

This paper describes a neural-based technique for detecting upright persons in low-resolution beach imagery in order to predict trends of tourist activities at beach sites. The proposed system uses a structural feature extraction technique to represent objects of interest for training a selection of neural classifiers. A number of neural-based classifiers are compared in this study and a direction-based feature extraction technique is investigated in conjunction with a rotationally invariant procedure for the purpose of beach object classification. Encouraging results are presented for person detection using video imagery collected from a beach site on the coast of Australia.