SHAPE RECOVERY AND ERROR CORRECTION BASED ON HYPOTHETICAL CONSTRAINTS BY PARALLEL NETWORK FOR ENERGY MINIMIZATION

1994 ◽  
pp. 163-179
Author(s):  
KOH KAKUSHO ◽  
SEIICHIRO DAN ◽  
NORIHIRO ABE ◽  
TADAHIRO KITAHASHI
Keyword(s):  
Error Correction ◽  
Energy Minimization ◽  
Shape Recovery ◽  
Parallel Network

SHAPE RECOVERY AND ERROR CORRECTION BASED ON HYPOTHETICAL CONSTRAINTS BY PARALLEL NETWORK FOR ENERGY MINIMIZATION

1994 ◽  
Vol 08 (02) ◽  
pp. 577-593
Author(s):  
KOH KAKUSHO ◽  
SEIICHIRO DAN ◽  
NORIHIRO ABE ◽  
TADAHIRO KITAHASHI
Keyword(s):  
Energy Minimization ◽  
Shape Recovery ◽  
Three Dimensional ◽  
Input Image ◽  
Model Driven ◽  
Optical Projection ◽  
Monocular Image ◽  
Parallel Network ◽  
3D Shape Recovery ◽  
Additional Constraints

Three-dimensional (3D) shape recovery from a monocular image is the inverse process of optical projection and necessitates the use of additional constraints on 3D features of the objects. We have proposed the method of shape recovery based on some hypothetical constraints and its realization by energy minimization using a parallel network. In this paper, we will discuss an extension of our proposal with the aim of correcting noise and errors in an input image through the process of shape recovery. It is hardly possible to extract edges and vertexes free from noise and errors from a real image. For the robustness of the system, we must provide our system with the ability to correct such noise and errors. In this extension, we can also modulate the inclination of the process toward model-driven or data-driven.

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