چکیده مقاله
We introduce a new variational framework for optical flow estimation that jointly accounts for occlusions and smooth yet discontinuity preserving motion fields Classic TV L1 approaches often struggle where brightness constancy fails—such as at occlusions—and may produce undesirable “staircase” artifacts due to first order total variation regularization To tackle these limitations, we propose an occlusion aware formulation in which each pixel is assigned a mask variable indicating whether it should adhere to brightness constancy Simultaneously, we replace the standard TV term with a second order total generalized variation TGV prior, allowing the estimated flow to transition smoothly within objects while preserving sharp boundaries The resulting convex energy is efficiently minimized via a primal dual algorithm, embedded in a coarse to fine warping strategy for handling large displacements Experiments on synthetic and real datasets, including Middlebury and KITTI, show that our method outperforms classical TV L1 in occluded areas and yields more realistic flow fields with reduced staircasing These results demonstrate the benefits of pairing explicit occlusion handling with second order regularization in a unified optical flow framework
کلیدواژهها
نویسندگان
Hossein Choubin
Tarbiat Modares University, Faculty of Computer Science
شیوه ارجاع
Choubin, Hossein,1403,Occlusion-Aware TV-L1 Optical Flow with Second-Order Regularization,The 5th international conference on artificial intelligence and its future prospects in electrical, computer, mechanical and telecommunication engineering sciences,Mashhad
ارائهشده در
مجموعه مقالات پنجمین کنفرانس بین المللی هوش مصنوعی و چشم انداز آینده آن در علوم مهندسی برق ، کامپیوتر ، مکانیک و مخابرات17 اسفند 1403 · مشهد