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Terrain Geometry from Monocular Image Sequences
Alexander Mckenzie,Eugene Vendrovsky,Junyong Noh 한국정보과학회 2008 Journal of Computing Science and Engineering Vol.2 No.1
Terrain reconstruction from images is an ill-posed, yet commonly desired Structure from Motion task when compositing visual effects into live-action photography. These surfaces are required for choreography of a scene, casting physically accurate shadows of CG elements, and occlusions. We present a novel framework for generating the geometry of landscapes from extremely noisy point cloud datasets obtained via limited resolution techniques, particularly optical flow based vision algorithms applied to live-action video plates. Our contribution is a new statistical approach to remove erroneous tracks ('outliers') by employing a unique combination of well established techniques-including Gaussian Mixture Models (GMMs) for robust parameter estimation and Radial Basis Functions (RBFs) for scattered data interpolation-to exploit the natural constraints of this problem. Our algorithm offsets the tremendously laborious task of modeling these landscapes by hand, automatically generating a visually consistent, camera position dependent, thin-shell surface mesh within seconds for a typical tracking shot.
Terrain Geometry from Monocular Image Sequences
McKenzie, Alexander,Vendrovsky, Eugene,Noh, Jun-Yong Korean Institute of Information Scientists and Eng 2008 Journal of Computing Science and Engineering Vol.2 No.1
Terrain reconstruction from images is an ill-posed, yet commonly desired Structure from Motion task when compositing visual effects into live-action photography. These surfaces are required for choreography of a scene, casting physically accurate shadows of CG elements, and occlusions. We present a novel framework for generating the geometry of landscapes from extremely noisy point cloud datasets obtained via limited resolution techniques, particularly optical flow based vision algorithms applied to live-action video plates. Our contribution is a new statistical approach to remove erroneous tracks ('outliers') by employing a unique combination of well established techniques-including Gaussian Mixture Models (GMMs) for robust parameter estimation and Radial Basis Functions (REFs) for scattered data interpolation-to exploit the natural constraints of this problem. Our algorithm offsets the tremendously laborious task of modeling these landscapes by hand, automatically generating a visually consistent, camera position dependent, thin-shell surface mesh within seconds for a typical tracking shot.
( Alexander Balmaceda ),( Sona Arora ),( Ilan Sondheimer ),( Mckenzie M. Hollon ) 대한외상학회 2019 大韓外傷學會誌 Vol.32 No.4
Extreme acidosis is a life-threatening physiological state that causes disturbances in the cardiovascular, pulmonary, immune, and hematological systems. Trauma patients commonly present to the operating room (OR) in hypovolemic shock, leading to tissue hypoperfusion and the development of acute metabolic acidosis with or without a respiratory component. It is often believed that trauma patients presenting to the OR in severe metabolic acidosis (pH <7.0) will have a nearly universal mortality rate despite aggressive resuscitation and damage control. The current literature does not include reports of successful resuscitations from a lower pH, which may lead providers to assume that a good outcome is not possible. However, here we describe a case of successful resuscitation from an initial pH of 6.5 with survival to discharge home 95 days after admission with almost full recovery. We describe the effects of acute acidosis on the respiratory and cardiovascular systems and hemostasis. Finally, we discuss the pillars of management in patients with extreme acute acidosis due to hemorrhage: transfusion, treatment of hyperkalemia, and consideration of buffering acidosis with bicarbonate and hyperventilation.