Writers: Henry Roncancio, André C. Hernandes, Marcelo Becker
Abstract: training; pipelines; accuracy
Abstract: This paper presents an exploration of the ceiling analysis of machine learning systems. It also provides an approach to the development of pedestrian recognition systems using this analysis. A pedestrian detection pipeline is simulated in order to evaluate this method. The advantage of this method is that it allows determining the most promising pipeline’s elements to be modified as a way of more efficiently improving the recognition system. The pedestrian recognition is based on computer vision and is intended for an autonomous car application. A Linear SVM used as classifier enables the recognition, so this development is also addressed as a machine learning problem. This analysis concludes that for this application the more worthy path to be followed is the improvement of the pre-processing method instead of the classifier.
