Title :
Quantitative measures of change based on feature organization: eigenvalues and eigenvectors
Author :
Sarkar, Sudeep ; Boyer, Kim L.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL, USA
Abstract :
We propose four measures of image organizational change which can be used to monitor construction activity. The measures are based on the thesis that the progress of construction will see a change in the individual image feature attributes as well as an evolution in the relationships among these features. This change in the relationship is captured by the eigenvalues and eigenvectors of the relation graph embodying the organization among the image features. We demonstrate the ability of the measures to differentiate between no development, the onset of construction, and full development, on the available real test image set
Keywords :
eigenvalues and eigenfunctions; feature extraction; eigenvalues; eigenvectors; feature organization; image feature attributes; image organizational change; quantitative measures; Airplanes; Buildings; Computer science; Eigenvalues and eigenfunctions; Face recognition; Image edge detection; Image segmentation; Motion estimation; Roads; Statistics;
Conference_Titel :
Computer Vision and Pattern Recognition, 1996. Proceedings CVPR '96, 1996 IEEE Computer Society Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-8186-7259-5
DOI :
10.1109/CVPR.1996.517115