360° Optical Flow using Tangent Images
원문 초록
Omnidirectional 360{\deg} images have found many promising and exciting applications in computer vision, robotics and other fields, thanks to their increasing affordability, portability and their 360{\deg} field of view. The most common format for storing, processing and visualising 360{\deg} images is equirectangular projection (ERP). However, the distortion introduced by the nonlinear mapping from 360{\deg} image to ERP image is still a barrier that holds back ERP images from being used as easily as conventional perspective images. This is especially relevant when estimating 360{\deg} optical flow, as the distortions need to be mitigated appropriately. In this paper, we propose a 360{\deg} optical flow method based on tangent images. Our method leverages gnomonic projection to locally convert ERP images to perspective images, and uniformly samples the ERP image by projection to a cubemap and regular icosahedron vertices, to incrementally refine the estimated 360{\deg} flow fields even in the presence of large rotations. Our experiments demonstrate the benefits of our proposed method both quantitatively and qualitatively.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
MEMFOF: High-Resolution Training for Memory-Efficient Multi-Frame Optical Flow Estimation
WAFT: Warping-Alone Field Transforms for Optical Flow
Multimodal Fusion SLAM with Fourier Attention
EndoMUST: Monocular Depth Estimation for Robotic Endoscopy via End-to-end Multi-step Self-supervised Training
MOL: Joint Estimation of Micro-Expression, Optical Flow, and Landmark via Transformer-Graph-Style Convolution
Inference-Time Gaze Refinement for Micro-Expression Recognition: Enhancing Event-Based Eye Tracking with Motion-Aware Post-Processing
토론
이 논문과 연결된 포럼 글이 아직 없습니다.