A shape comparison reinforcement method based on feature extractors and F1-Score
Evaluating object segmentation is a topic of great interest for shape comparison techniques. In this work, ad-hoc metrics for a detailed segmentation analysis and a novel keypoint based method for comparing pairs of shapes are presented. As references, two different segmentation approaches were used: a handmade segmentation and an automatic one based on a Convolutional Neural Network (CNN). The proposed comparison approach consists of a combination between a keypoint extractor and an invariant scale shape identifier.