Retrieval and Clustering from a 3D Human Database based on Body and Head Shape

TL;DR

This paper presents a practical framework for retrieving and clustering 3D human body data based on combined body and head shape similarity, using the CAESAR database and a web interface.

Contribution

It introduces a novel similarity-based retrieval system that considers both body and head shapes, enabling efficient querying in a large 3D human database.

Findings

Effective retrieval within reasonable time

Utilizes the CAESAR anthropometric database

Provides a web-based interactive interface

Abstract

In this paper, we describe a framework for similarity based retrieval and clustering from a 3D human database. Our technique is based on both body and head shape representation and the retrieval is based on similarity of both of them. The 3D human database used in our study is the CAESAR anthropometric database which contains approximately 5000 bodies. We have developed a web-based interface for specifying the queries to interact with the retrieval system. Our approach performs the similarity based retrieval in a reasonable amount of time and is a practical approach.