Robust Real-Time Visual Odometry for Stereo Endoscopy Using Dense Quadrifocal Tracking

Visual tracking in endoscopic scenes is known to be a difficult task due to the lack of textures, tissue deformation and specular reflection. In this paper, we devise a real-time visual odometry framework to robustly track the 6-DoF stereo laparoscope pose using the quadrifocal relationship. The instant motion of a stereo camera creates four views which can be constrained by the quadrifocal geometry. Using the previous stereo pair as a reference frame, the current pair can be warped back by minimising a photometric error function with respect to a camera pose constrained by the quadrifocal geometry. Using a robust estimator can further remove the outliers caused by occlusion, deformation and specular highlights during the optimisation. Since the optimisation uses all pixel data in the images, it results in a very robust pose estimation even for a textureless scene. The quadrifocal geometry is initialised by using real-time stereo reconstruction algorithm which can be efficiently parallelised and run on the GPU together with the proposed tracking framework. Our system is evaluated using a ground truth synthetic sequence with a known model and we also demonstrate the accuracy and robustness of the approach using phantom and real examples of endoscopic augmented reality.