Results 251 to 260 of about 60,644 (302)

GL-VSLAM: A General Lightweight Visual SLAM Approach for RGB-D and Stereo Cameras. [PDF]

Sensors (Basel)
Li X, Li T, Zhang Y, Li Z, Ban L, Ning Y.   +5 more
europepmc   +1 more source

ES-ATRK: A Global Bundle Adjustment Initialisation Method for Event-Based Stereo Visual Inertial SLAM System Using Adaptive Threshold Robust Kernel Functions. [PDF]

Sensors (Basel)
Zhao J, Yu H, Zhang Z, Li Y, Zhu H, Yan X, Wang J.   +6 more
europepmc   +1 more source

Non-Contact IOP Estimation Based on Corneal Stress Birefringence: Experimental and Computational Validation. [PDF]

Sensors (Basel)
Li H, Li Y, Guo Z, Zhang Y.
europepmc   +1 more source

Application of LSTM-CNN in skiing action recognition under artificial intelligence technology. [PDF]

Sci Rep
Zhang W, Xu L, Wang L.
europepmc   +1 more source

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Occlusion-Aware Optical Flow Estimation

IEEE Transactions on Image Processing, 2008
Optical flow can be reliably estimated between areas visible in two images, but not in occlusion areas. If optical flow is needed in the whole image domain, one approach is to use additional views of the same scene. If such views are unavailable, an often-used alternative is to extrapolate optical flow in occlusion areas.
Janusz Konrad
exaly   +3 more sources

Constrained Optical Flow Estimation as a Matching Problem

IEEE Transactions on Image Processing, 2013
In general, discretization in the motion vector domain yields an intractable number of labels. In this paper, we propose an approach that can reduce general optical flow to the constrained matching problem by pre-estimating a 2-D disparity labeling map of the desired discrete motion vector function.
M G Mozerov
exaly   +3 more sources

Optical flow and scene flow estimation: A survey

Pattern Recognition, 2021
Abstract Motion analysis is one of the most fundamental and challenging problems in the field of computer vision, which can be widely applied in many areas, such as autonomous driving, action recognition, scene understanding, and robotics. In general, the displacement field between subsequent frames can be divided into two types: optical flow and ...
Mingliang Zhai, Xuezhi Xiang, Ning Lv 0001, Xiangdong Kong   +3 more
openaire   +1 more source

SSTM: Spatiotemporal recurrent transformers for multi-frame optical flow estimation

Neurocomputing, 2023
Inaccurate optical flow estimates in and near occluded regions, and out-of-boundary regions are two of the current significant limitations of optical flow estimation algorithms.
Madhusudhanan Balasubramanian
exaly   +3 more sources

Estimating fluid optical flow

Proceedings 15th International Conference on Pattern Recognition. ICPR-2000, 2002
We address the problem of fluid motion estimation in image sequences. For such motions, standard optical flow methods, based on intensity conservation and spatial coherence of motion field, are not suitable. This is due to the highly deformable nature of a fluid medium.
Thomas Corpetti, Étienne Mémin, Patrick Pérez   +2 more
openaire   +1 more source