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Real-Time Feature Matching for the Accurate Recovery of Augmented-Reality Display in Laparoscopic Videos

  • Conference paper
Augmented Environments for Computer-Assisted Interventions (AE-CAI 2012)

Abstract

Augmented-Reality (AR) displays increase surgeon’s visual awareness of high-risk surgical targets (e.g., the location of a tumor) by accurately overlaying pre-operative radiological 3-D model onto the intra-operative laparoscopic video. Existing AR systems are not robust to sudden camera motion or prolonged occlusions, which can cause the loss of those anchor points tracked along the video sequence, and thus the loss of the AR display. In this paper, we present a novel AR system, integrated with a novel feature-matching method, to automatically recover the lost augmentation by predicting the image locations of the AR anchor image-points after sudden image changes. Extensive experiments on challenging surgical video data are presented that show the accuracy, speed, and robustness of our designs.

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Puerto-Souza, G.A., Castaño-Bardawil, A., Mariottini, GL. (2013). Real-Time Feature Matching for the Accurate Recovery of Augmented-Reality Display in Laparoscopic Videos. In: Linte, C.A., Chen, E.C.S., Berger, MO., Moore, J.T., Holmes, D.R. (eds) Augmented Environments for Computer-Assisted Interventions. AE-CAI 2012. Lecture Notes in Computer Science, vol 7815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38085-3_15

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  • DOI: https://doi.org/10.1007/978-3-642-38085-3_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38084-6

  • Online ISBN: 978-3-642-38085-3

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