Video Object Tracking by Feature Point Descriptor and Template Matching

Abstract

The present research focuses on developing a method based on feature point descriptors and template matching and comparing its performance with a method based on deep learning. These methods have particular aspects in how they were implemented; some stand out for the simplicity of their structure and others for the complexity they entail. The methods presented in this work range from developing a basic template matching algorithm, developing an algorithm based on feature point descriptors incorporating the template matching qualities to obtain better results, to implementing a method based on deep learning. Performance and precision tests are carried out to compare the methods on a selected dataset of video object tracking.