Methods and apparatuses for video segmentation, classification, and retrieval using image class statistical models
US6751354B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Mar 11, 1999 |
| Grant date | Jun 15, 2004 |
| Priority date | — |
| Expiry date | Mar 11, 2019 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/85
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques for classifying video frames using statistical models of transform coefficients are disclosed. After optionally being decimated in time and space, image frames are transformed using a discrete cosine transform or Hadamard transform. The methods disclosed model image composition and operate on grayscale images. The resulting transform matrices are reduced using truncation, principal component analysis, or linear discriminant analysis to produce feature vectors. Feature vectors of training images for image classes are used to compute image class statistical models. Once image class statistical models are derived, individual frames are classified by the maximum likelihood resulting from the image class statistical models. Thus, the probabilities that a feature vector derived from a frame would be produced from each of the image class statistical models are computed. The frame is classified into the image class corresponding to the image class statistical model which produced the highest probability for the feature vector derived from the frame. Optionally, frame sequence information is taken into account by applying a hidden Markov model to represent image class transitions…
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.