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Related Experiment Video

Updated: Jan 14, 2026

Quantification of Oculomotor Responses and Accommodation Through Instrumentation and Analysis Toolboxes
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MOTT modular optical tool tracking framework enabling efficient benchmarking.

Federico Salerno1, Alessandro Contenti2, Luca Ulrich2

  • 1Department of Production and Management Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129, Turin, Italy. federico.salerno@polito.it.

Scientific Reports
|October 24, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces the Modular Optical Tool Tracking (MOTT) framework, a unified platform for developing and benchmarking optical tracking systems. MOTT simplifies the integration and comparison of diverse tracking methods for applications in robotics and augmented reality.

Keywords:
BenchmarkingModular frameworkOptical trackingPose estimationQFDTool tracking

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Area of Science:

  • Computer Vision
  • Robotics
  • Software Engineering

Background:

  • Optical tool tracking determines an object's 6DoF pose in real-time using visual data.
  • Current systems often have tight hardware-software integration, hindering management and benchmarking.
  • Standardized evaluation is needed for diverse optical tracking solutions.

Purpose of the Study:

  • To present the Modular Optical Tool Tracking (MOTT) framework, a unified platform for implementing, integrating, and benchmarking optical tracking solutions.
  • To address the complexity and lack of standardization in current optical tracking systems.
  • To provide a flexible and extensible architecture for optical tracking method development.

Main Methods:

  • Adopted a requirement-based design approach using Quality Function Deployment (QFD).
  • Developed a software framework with a flexible, object-oriented architecture.
  • Implemented and evaluated two marker-based tracking methods using an RGB camera.

Main Results:

  • The MOTT framework enables standardized implementation and comparison of optical tracking methods.
  • Case studies demonstrated framework utility for method integration and performance analysis.
  • Computational metrics (frame rate, CPU/memory usage) and pose visualizations were reported.

Conclusions:

  • The MOTT framework facilitates standardized evaluation and benchmarking of optical tracking systems.
  • It offers a foundation for future extensions, including non-optical tracking and large-scale studies.
  • The open-source implementation is available for community use and development.