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However, vasculature mosaic is challenging due to the fluctuating imaging conditions during fetoscopic surgery.<\/jats:p><\/jats:sec><jats:sec><jats:title>Method<\/jats:title><jats:p>A scene adaptive feature\u2010based approach for image correspondence in free\u2010hand endoscopic placental video is proposed. It contributes towards existing techniques by introducing a failure detection method based on statistical attributes of the feature distribution, and an updating mechanism that self\u2010tunes parameters to recover from registration failures.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Validations on endoscopic image sequences of a phantom and a monkey placenta are carried out to demonstrate mismatch recovery. In two 100\u2010frame sequences, automatic self\u2010tuned results improved by 8% compared with manual experience\u2010based tuning and a slight 2.5% deterioration against exhaustive tuning (gold standard).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>This scene\u2010adaptive image correspondence approach, which is not restricted to a set of generalized parameters, is suitable for applications associated with dynamically changing imaging conditions. 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