Abstract: Strain localization is a precursor to the failure of geotechnical materials, widely present in the progressive failure process of geotechnical engineering, and has become an important research topic in the fields of geotechnical mechanics and engineering. Through literature research on existing strain localization testing methods, the application scope and characteristics of internal measurement techniques and surface measurement techniques in revealing the strain localization problem of geotechnical materials were summarized. Research has shown that internal measurement techniques such as computed tomography (CT), scanning electron microscopy (SEM), and digital volume correlation (DVC) have the advantage of obtaining high-resolution microstructure information of samples, while surface measurement techniques such as particle image velocimetry (PIV) and digital image correlation (DIC) are known for their ease of operation and real-time dynamic observation. At the same time, the development trend of strain localization testing technology for geotechnical materials has been discussed. On the one hand, the collaborative application of multiple testing technologies was emphasized, and multi physical field information was introduced to reveal the progressive failure law of geotechnical materials from multiple scales and dimensions; On the other hand, by introducing artificial intelligence technology, efficient recognition of sample images obtained by CT, PIV, DIC and other technologies can be achieved. This approach holds promise for predicting the initiation and evolution of strain localization, thereby offering novel insights and technological pathways for disaster warning and prevention in geotechnical engineering.