Modular Tracking Framework: A Unified Approach to Registration based Tracking
Abhineet Singh, Martin Jagersand

TL;DR
The paper introduces the Modular Tracking Framework (MTF), an open source, efficient, and extensible system for registration-based tracking in robotics, enabling high precision, speed, and research flexibility through modular design.
Contribution
It presents a novel modular conceptualization of registration trackers and provides a versatile, extensible framework with numerous methods for improved tracking performance.
Findings
Faster and more precise than existing systems
Supports over 2000 distinct trackers with modular combinations
Eases integration and testing of new tracking methods
Abstract
This paper presents a modular, extensible and highly efficient open source framework for registration based tracking called Modular Tracking Framework (MTF). Targeted at robotics applications, it is implemented entirely in C++ and designed from the ground up to easily integrate with systems that support any of several major vision and robotics libraries including OpenCV, ROS, ViSP and Eigen. It implements more methods, is faster, and more precise than other existing systems. Further, the theoretical basis for its design is a new way to conceptualize registration based trackers that decomposes them into three constituent sub modules - Search Method (SM), Appearance Model (AM) and State Space Model (SSM). In the process, we integrate many important advances published after Baker \& Matthews' landmark work in 2004. In addition to being a practical solution for fast and high precision…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRobotics and Sensor-Based Localization · Genome Rearrangement Algorithms · Advanced Image and Video Retrieval Techniques
