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TOSD: A Hierarchical Object-Centric Descriptor Integrating Shape, Color, and Topology.

Jun-Hyeon Choi1, Jeong-Won Pyo2, Ye-Chan An1

  • 1Department of Electrical and Computer Engineering, College of Information and Communication Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea.

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Summary
This summary is machine-generated.

This study introduces the Triplet Object-Centric Semantic Descriptor (TOSD), a novel hierarchical framework for robust visual scene understanding. TOSD effectively integrates shape, color, and topology for improved object and scene representation across multiple abstraction levels.

Keywords:
feature aggregationhierarchical descriptorobject poolingscene understandingvisual representation

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Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Robotics

Background:

  • Existing pixel-based and global feature embedding methods have limitations in capturing complex scene semantics.
  • A need exists for a descriptor framework that supports multi-level reasoning and integrates diverse object attributes.
  • Previous work on the Semantic Modeling Framework established layered environment representations.

Purpose of the Study:

  • To introduce the Triplet Object-Centric Semantic Descriptor (TOSD), a hierarchical framework for object-centric scene representation.
  • To overcome limitations of current visual feature descriptors by integrating shape, color, and topological information.
  • To enable multi-level reasoning from low-level pixel details to high-level semantic structures.

Main Methods:

  • Developed a hierarchical object-centric descriptor framework (TOSD).
  • Integrated shape, color, and topological information at object and scene levels.
  • Created a representation with three abstraction levels: pixel, object, and semantic structure.

Main Results:

  • TOSD demonstrated competitive performance across multiple computer vision tasks.
  • The framework showed robustness against challenges like occlusion and viewpoint changes.
  • Achieved compact and consistent embeddings integrating local cues and global context.

Conclusions:

  • TOSD provides a unified and effective approach to hierarchical visual scene representation.
  • The method is versatile and applicable to a wide range of vision and robotics tasks.
  • This work advances semantic scene understanding through object-centric, multi-level feature integration.