Optical flow estimation is a fundamental problem on the computer vision. Recently, a few hundreds of optical flows can compute in a real-time on a common PC system, however, to extract dense flows such as 60000 flows, the method seems to take a long computation time. In this paper, we ...
This paper presents a flexible and scalable approach to the parallelization of the computation of optical flow. This approach is based on data parallel distribution. Images are divided into several subimages processed by a software pipeline while respecting dependencies between computation stages. The pa...
The computation of optical flow has been proposed as a pre-processing step for many high-level vision algorithms. One of the main approaches to the optical flow problem is the gradient-based approach which differentiates the image intensity to compute the optical flow. Often motion vectors ...
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(Section 4.2), and highlight the robustness of the proposed method which can deal with very different scenes and acquisition conditions (Section 4.3). The code (computation of homologous point groups usable as input by any SfM approach) and all data used in this section are given as ...
This new optical flow prior is compared with previous robust priors and is incorporated into a recent, accurate algorithm for dense optical flow computation. Experiments with natural and synthetic sequences illustrate how the learned optical flow prior quantitatively improves flow accuracy and how it ...
The hardware optical flow functionality in Turing GPUs helps all these use-cases by offloading the intensive flow-vector computation to a dedicated hardware engine on the GPU silicon. This frees up GPU and CPU cycles for other tasks. NVIDIA’s Optical Flow SDK exposes a new set of APIs which...
Owing to the presence of two neutrinos, the computation of the WW invariant mass is not possible. However, an associated variable, the transverse mass, mT, can be computed from the \({{\bf{p}}}_{{\rm{T}}}\) of the charged leptons and the ...
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