𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Symmetrical Dense Optical Flow Estimation with Occlusions Detection

✍ Scribed by Luis Alvarez; Rachid Deriche; Théo Papadopoulo; Javier Sánchez

Book ID
106559075
Publisher
Springer US
Year
2007
Tongue
English
Weight
695 KB
Volume
75
Category
Article
ISSN
0920-5691

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Computation of Dense Optical Flow with a
Computation of Dense Optical Flow with a Parametric Smoothness Model
✍ Navid Haddadi; C.-C.Jay Kuo 📂 Article 📅 1993 🏛 Elsevier Science 🌐 English ⚖ 888 KB

A new algorithm is presented for the computation of dense optical flow and motion boundaries from an image sequence using two or more frames. The algorithm is based on a novel parametric smoothness model; it decomposes optical flow into irrotational and solenoidal fields, and imposes the smoothness

Detection of moving objects using observ
Detection of moving objects using observer motion-based optical flow estimation
✍ Takumi Ebine; Nozomu Hamada 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 280 KB

## Abstract A scheme for detecting a moving object in a three‐dimensional environment from observed dynamic images by optical flow, based on the state of the motion of the observing system, is proposed in this paper. The usual optical flow constraint equations defined in an image coordinate system

Estimating optical flow with cellular ne
Estimating optical flow with cellular neural networks
✍ Shi, B. E.; Roska, T.; Chua, L. O. 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 412 KB 👁 2 views

The cellular neural network is a locally interconnected neural network capable of high-speed computation when implemented in analog VLSI. This work describes a CNN algorithm for estimating the optical flow from an image sequence. The algorithm is based on the spatio-temporal filtering approach to im