Azhar Quddus, Senior Computer Vision Engineer at Au-Zone Technologies, presents the “Understanding DNN-Based Object Detectors” tutorial at the May 2022 Embedded Vision Summit.
Unlike image classifiers, which merely report on the most important objects within or attributes of an image, object detectors determine where objects of interest are located within an image. Consequently, object detectors are central to many computer vision applications including (but not limited to) autonomous vehicles and virtual reality.
In this presentation, Quddus provides a technical introduction to deep-neural-network-based object detectors. He explains how these algorithms work, and how they have evolved in recent years, utilizing examples of popular object detectors. Quddus examines some of the trade-offs to consider when selecting an object detector for an application, and touches on accuracy measurement. He also discusses performance comparison among the models discussed in this presentation.
See here for a PDF of the slides.
