ARTOS -- Adaptive Real-Time Object Detection System

TL;DR

ARTOS is an easy-to-use, real-time object detection system that simplifies model creation and adaptation with minimal manual effort, fast learning, and a user-friendly GUI, suitable for integration into various applications.

Contribution

It introduces a user-friendly GUI and fast learning techniques for quick creation and adaptation of object detection models without extensive manual data annotation.

Findings

Reduces manual annotation effort

Enables quick model adaptation to new domains

Provides fast learning for real-time detection

Abstract

ARTOS is all about creating, tuning, and applying object detection models with just a few clicks. In particular, ARTOS facilitates learning of models for visual object detection by eliminating the burden of having to collect and annotate a large set of positive and negative samples manually and in addition it implements a fast learning technique to reduce the time needed for the learning step. A clean and friendly GUI guides the user through the process of model creation, adaptation of learned models to different domains using in-situ images, and object detection on both offline images and images from a video stream. A library written in C++ provides the main functionality of ARTOS with a C-style procedural interface, so that it can be easily integrated with any other project.