초록 ▼

Methods and apparatus for detecting instances of a selected object or object feature in a digitally represented scene utilize analysis of probability densities to determine whether an input image (or portion thereof) represents such an instance. The invention filters images of objects that, although

Methods and apparatus for detecting instances of a selected object or object feature in a digitally represented scene utilize analysis of probability densities to determine whether an input image (or portion thereof) represents such an instance. The invention filters images of objects that, although in some ways similar to the object under study, fail to qualify as typical instances of that object. The invention is useful in the detection and recognition of virtually any multifeatured entity such as human faces, features thereof (e.g., eyes), as well as non-rigid and articulated objects such as human hands.

대표청구항 ▼

[ What is claimed is:] [1.] A method for detecting selected features in digitally represented input images, the method comprising the steps of:a. representing a training set of instances of the selected feature as a set of eigenvectors in a multidimensional image space;b. representing portions of th

[ What is claimed is:] [1.] A method for detecting selected features in digitally represented input images, the method comprising the steps of:a. representing a training set of instances of the selected feature as a set of eigenvectors in a multidimensional image space;b. representing portions of the input image as input vectors in the image space;c. performing a density-estimation analysis on the input vectors to estimate, for each input vector, a probability level indicative of the likelihood that the input vector corresponds to an image portion containing an instance of the selected feature, wherein said density estimation analysis is based on all vector components; andd. identifying image portions having the highest associated probability levels.