IST-ROS: A flexible object segmentation and tracking framework for robotics applications

Abstract

Object detection and tracking are crucial components in the development of various applications and research endeavors within the computer science and robotics community. However, the diverse shapes and appearances of real-world objects, as well as dynamic nature of the scenes, may pose significant challenges for these tasks. Existing object detection and tracking methods often require extensive data annotation and model re-training when applied to new objects or environments, diverting valuable time and resources from the primary research objectives. In this paper, we present IST-ROS, Interactive Segmentation and Tracking for ROS, a software solution that leverages the capabilities of the Segment Anything Model (SAM) and semi-supervised video object segmentation methods to enable flexible and efficient object segmentation and tracking. Its graphical interface allows interactive object selection and segmentation using various prompts, while integrated tracking ensures robust performance even under occlusions and object interactions. By providing a flexible solution for object segmentation and tracking, IST-ROS aims to facilitate rapid prototyping and advancement of robotics applications.