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Analytical Review of Event-Based Camera Depth Estimation Methods and Systems
Justas Furmonas1, John Liobe1, Vaidotas Barzdenas1
1Department of Computer Science and Communications Technologies, Vilnius Gediminas Technical University, 03227 Vilnius, Lithuania.
Sensors (Basel, Switzerland)
|February 15, 2022
Summary
Event-based cameras offer superior performance over traditional frame-based cameras. This review analyzes existing event-based depth estimation methods, highlighting a need for further development in this sparse research area.
Area of Science:
- Computer Vision
- Robotics
- Sensor Technology
Background:
- Event-based cameras (EBCs) are gaining traction due to their high performance, surpassing traditional frame-based cameras in many applications.
- Despite their advantages, EBCs for depth estimation remain an under-explored area.
Purpose of the Study:
- To provide a comprehensive summary of current event-based camera systems for depth estimation.
- To analytically review existing methods and identify research gaps.
Main Methods:
- Literature review of published event-based depth estimation methods and systems.
- Analytical assessment of the summarized techniques.
Main Results:
- Identified a limited number of existing event-based depth estimation instantiations.
- Highlighted the performance advantages of EBCs over frame-based cameras.
Conclusions:
- The field of event-based depth estimation requires significant further research and development.
- Recommendations for future advancements in EBC depth estimation are provided.
