Repetitive Patterns Recognition in Textures of Ancient Peruvian Pottery-Reference-Cited by-同舟云学术

Repetitive Patterns Recognition in Textures of Ancient Peruvian Pottery

Published:2024-09-06 Issue: Volume: Page:
ISSN:1556-4673
Container-title:Journal on Computing and Cultural Heritage
language:en
Short-container-title:J. Comput. Cult. Herit.

Author:

Sepulveda Sebastian¹^ORCID,Bustos Benjamin¹^ORCID,Sipiran Ivan²^ORCID

Affiliation:

1. IMFD, Department of Computer Science, University of Chile, Chile

2. Department of Computer Science, University of Chile, Chile

Abstract

We present a study and comparison of computer vision methods for the task of finding repetitive motifs in ancient Peruvian pottery. Under this context, the main difficulties for solving the task are that the motifs are in most cases highly repetitive, that the motifs corresponding to the same pattern are slightly different due to be hand-drawn, and that the amount of data available for training and testing purposes is scarce. We evaluate and compare several techniques: Template Matching, Segment Anything Model, Mask R-CNN, Faster R-CNN, RetinaNet, and YoloV8-s. We conclude that YoloV8-s and Retina-Net are the most effective techniques for the task, but the effectiveness for zero-shot detection is low for all evaluated techniques.

Publisher

Association for Computing Machinery (ACM)

Link

https://dl.acm.org/doi/pdf/10.1145/3694789

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