Accession Number:

ADA413389

Title:

Learning Integrated Visual Database for Image Exploitation

Descriptive Note:

Final rept. 15 May 1997-31 Aug 2002

Corporate Author:

CALIFORNIA UNIV RIVERSIDE CENTER FOR RESEARCH IN INTELLIGENT SYSTEMS

Personal Author(s):

Report Date:

2002-11-25

Pagination or Media Count:

22.0

Abstract:

The research summarized in this report is aimed at developing image understanding IU algorithms and systems that have performance prediction and learning capabilities and that can improve their performance with experience, in terms of quality of results, processing speed and matching with the users perception. The following scientific problems are addressed a Fundamental theory for predicting the performance of object recognition systems and its validation on SAR images, b Automatic methods for recognizing articulated, occluded and configuration variants of targets in SAR images and video, c Adaptive learning integrated target recognition algorithmssystems, and d Learning visual concepts in imagesvideos with user interaction and experience over time. The research presented makes a significant contribution to real-world applications which require robust high performance automated systems that can recognize objects in reconnaissance imagery acquired under dynamically changing conditions and for systems that can efficiently extract meaningful information from enormous imagevideo databases.

Subject Categories:

  • Active and Passive Radar Detection and Equipment

Distribution Statement:

APPROVED FOR PUBLIC RELEASE