DocumentCode
1677109
Title
Displacement vector estimation with cellular neural networks
Author
Feiden, Dirk ; Tetzlaff, Ronald
Author_Institution
Inst. of Appl. Phys., Frankfurt Univ., Germany
Volume
3
fYear
2002
fDate
6/24/1905 12:00:00 AM
Firstpage
2049
Lastpage
2052
Abstract
Displacement vector estimation is one of the open key problems in computer vision and video coding. For example, in computer vision, displacement vector estimation is usually the basis of some kind of motion estimation. Unfortunately, displacement vector estimation using statistical methods is always computationally complex, which might be a restriction in real-time processing. In this paper, we show that displacement vector estimation can be efficiently performed by using cellular neural networks (CNNs). In order to find CNN templates, therefore, we have used the new optimization method of iterative annealing
Keywords
cellular neural nets; computational complexity; computer vision; estimation theory; iterative methods; motion estimation; real-time systems; simulated annealing; vectors; video coding; cellular neural networks; computational complexity; computer vision; displacement vector estimation; iterative annealing; motion estimation; optimization method; real-time processing; statistical methods; templates; video coding; Cellular neural networks; Computer vision; Couplings; Motion estimation; Neural networks; Object detection; Optimization methods; Physics; Polynomials; Video coding;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location
Honolulu, HI
ISSN
1098-7576
Print_ISBN
0-7803-7278-6
Type
conf
DOI
10.1109/IJCNN.2002.1007455
Filename
1007455
Link To Document