Superpixel Segmentation: From Theory to Applications

• Isabela Borlido PUC Minas
• Felipe Belém PUC Minas / UNICAMP
• Leonardo Melo UNICAMP
• Taylla M. Theodoro UNICAMP
• Ilan F. Silva UNICAMP
• Zenilton K. G. do Patrocínio PUC Minas
• Alexandre X. Falcão UNICAMP
• Silvio Jamil F. Guimarães PUC Minas

Resumo

Superpixel segmentation consists of partitioning images into regions composed of similar and connected pixels. Its methods have been widely used in many computer vision applications since it allows for reducing the workload, removing redundant information, and preserving regions with meaningful features. Due to the rapid progress in this area, the literature fails to catch up on more recent works among the compared ones and to categorize the methods according to all existing strategies. We revisit the recent and popular literature according to our taxonomy and evaluate 20 strategies based on nine criteria: connectivity, compactness, delineation, control over the number of superpixels, color homogeneity, robustness, running time, stability, and visual quality. Thus, this document presents a proposal for a tutorial to be presented at SIBGRAPI 2023.

Palavras-chave: Superpixel, Trends, Applications