Wyniki wyszukiwania - BazTech

1

Application of cascading two-dimensional canonical correlation analysis to image matching

Forczmański P., Kukharev G., Kamenskaya E.

Control and Cybernetics

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2011

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Vol. 40, no 3

833-848

EN

The paper presents a novel approach to Canonical Correlation Analysis (CCA) applied to visible and thermal infrared spectrum facial images. In the typical CCA framework biometrical information is transformed from original feature space into the space of canonical variates, and further processing takes place in this space. Extracted features are maximally correlated in canonical variates space, making it possible to expose, investigate and model latent relationships between measured variables. In the paper the CCA is implemented along two directions (along rows and columns of pixel matrix of dimension M x N) using a cascade scheme. The first stage of transformation proceeds along rows of data matrices. Its results are reorganized by transposition. These reorganized matrices are inputs to the second processing stage, namely basic CCA procedure performed along the rows of reorganized matrices, resulting in fact in proceeding along the columns of input data matrix. The so called cascading 2DCCA method also solves the Small Sample Size problem, because instead of the images of size MxN pixels in fact we are using N images of size M x 1 pixels and M images of size 1 x N pixels. In the paper several numerical experiments performed on FERET and Equinox databases are presented.

2

Two-dimensional canonical correlation analysis for face image processing and recognition

Kukharev G., Kamenskaya E.

Metody Informatyki Stosowanej

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2009

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nr 3 (20)

103-112

EN

Paper presents the method of two-dimensional canonical correlation analysis (2DCCA) as applied to image processing and biometrics. Method is based on representing the image as the sets of its rows (r) and columns (c) and implementation of CCA using these sets (for these reason we named the method as CCArc). CCArc features simple implementation and lesser complexity than other known approaches. In applications to biometrics CCArc is suitable to solving the problems when dimension of images (dimension of feature space) is greater than number of images, i.e. Small Sample Size problem (SSS). Demonstrated high efficiency of CCArc method for a number of computer experiments. Experiments itself are described with compact notation allowing to use its results in the framework of meta-analysis.

3

Systemy rozpoznawania twarzy dla obrazów widzialnych i podczerwieni z wykorzystaniem CCA

Szaber M., Kamenskaya E.

Metody Informatyki Stosowanej

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2008

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nr 3 (Tom 16)

223--236

EN

Face recognition systems based on visual images have reached a significant level of maturity with some practical success. However, the performance of visual face recognition may degrade under poor illumination conditions and in completely darkness. Infrared images represent a viable alternative to visible images in the search for practical face recognition. In the article, we investigate the face recognition scheme where category of identified face images differs from that stored in face database. CCA (Canonical Correlation Analysis) method is used to build face recognition system with using visual and infrared images. Next, we considered three scenarios for this kind of system: during a day, at night and at dusk. We presented CCA method for this system that is proper for this tasks the schemes of scenario and examples of their working.

4

Some aspects of automated psychological characteristics recognition from the facial image

Kamenskaya E., Kukharev G.

Metody Informatyki Stosowanej

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2008

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nr 2 (Tom 15)

29-37

EN

Identification of psychological characteristics is a task widely used in theoretical and practical psychological research, education, coaching, career guidance and hiring process, business and political affairs, psychotherapeutic diagnostics, self-exploration and awareness, etc. The. paper contains some, consideration of the computer system of automated psychological characteristics recognition from the facial image, such as a basic schema of its operation, image processing and analysts methods which can be applied, holistic and feature-based approaches, image databases for experiments, etc.

5

Recognition of Psychological Characteristics from Face

Kamenskaya E., Kukharev G.

Metody Informatyki Stosowanej

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2008

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nr 1 (Tom 13)

59-73

EN

Tht nature of computer vision causes the fact that not only computer science researchers are interested in it, but neuroscientists and psychologists, too. Ont of the main interests for psychology is identification of person's psychological traits and personality types which can be accomplished by different means of psychological testing: questionnaires, interviews, direct observations, etc. Though that is a general tendency of people to read character into a person's physical form, especially face. in relation to psychological characteristics recognition, face provides researchers and psychologists with instrument of obtaining information about personality and psychological traits that would be much more, objective than questionnaires and in iiropsychological tests and could be obtained remotely using person's facial portrait, with no need for personal, involvement The paper describes approaches to psychological characteristics recognition from facial image such us physiognomy, phase facial portrait, ophthalmogeometry, and explains the need in automating it.