Pace recognition: eigenface, elastic matching, and neural nets

Zhang, Jun; Yan, Yong; Lades, Martin

doi:10.1109/5.628712

Cited by 321 publications

(154 citation statements)

References 13 publications

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“…Some examples of identifying biometric features being used for identification based systems include hand geometry, thermal patterns in the face, blood vessel patterns in the retina and hand, finger and voice prints, and handwritten signatures (see [4,6,7,13,15,22,24]). Today, a few devices based on these biometric techniques are commercially available.…”

Section: Let Us See Your Hands Eyes and Facementioning

confidence: 99%

Keystroke dynamics as a biometric for authentication

Monrose

Rubin

2000

Future Generation Computer Systems

576

301

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More than ever before the Internet is changing computing as we know it. Global access to information and resources is becoming an integral part of nearly every aspect of our lives. Unfortunately, with this global network access comes increased chances of malicious attack and intrusion. In an effort to confront the new threats unveiled by the networking revolution of the past few years reliable, rapid, and unintrusive means for automatically recognizing the identity of individuals are now being sought. In this paper we examine an emerging non-static biometric technique that aims to identify users based on analyzing habitual rhythm patterns in the way they type.

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Section: Let Us See Your Hands Eyes and Facementioning

confidence: 99%

Keystroke dynamics as a biometric for authentication

Monrose

Rubin

2000

Future Generation Computer Systems

576

301

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“…The average and worst results of 100 trials from linear subspace representations as well as SHSA ones are shown in Table 4. SHSA performance is significantly better than the corresponding linear subspace in the image space essentially because different lighting conditions and facial expressions make the pixel-wise representation not reliable for recognition (Zhang, Yan, & Lades, 1997). The results obtained here are also significantly better than those obtained in Zhang et al (1997) on the same dataset.…”

Section: Experimental Results For Recognitionmentioning

confidence: 65%

Intrinsic generalization analysis of low dimensional representations

2003

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Low dimensional representations of images impose equivalence relations in the image space; the induced equivalence class of an image is named as its intrinsic generalization. The intrinsic generalization of a representation provides a novel way to measure its generalization and leads to more fundamental insights than the commonly used recognition performance, which is heavily influenced by the choice of training and test data. We demonstrate the limitations of linear subspace representations by sampling their intrinsic generalization, and propose a nonlinear representation that overcomes these limitations. The proposed representation projects images nonlinearly into the marginal densities of their filter responses, followed by linear projections of the marginals. We use experiments on large datasets to show that the representations that have better intrinsic generalization also lead to better recognition performance. q

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“…Valentin et al [10] were focussing on neural networks; Chellappa et al [11] were focussing on psychophysics issues with respect to face recognition; Zhang et al [12] focussing on Eigen face, neural networks and elastic matching. Seong et al [13] have focussed on the area of facial recognition techniques with specific reference to two dimensional images in the infra-red spectra.…”

Section: Background Literaturementioning

confidence: 99%

Facial emotion detection technology: concept, marketing applications, business drivers and challenges

Joshi¹,

Damle²,

Kumar³

2018

IJET

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The manuscript should contain an abstract. The abstract should be self-contained and citation-free and should not exceed 200 words. The abstract should state the purpose, approach, results and conclusions of the work. The author should assume that the reader has some knowledge of the subject but has not read the paper. Thus, the abstract should be intelligible and complete in it-self (no numerical references); it should not cite figures, tables, or sections of the paper. The abstract should be written using third person instead of first person.

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Pace recognition: eigenface, elastic matching, and neural nets

Cited by 321 publications

References 13 publications

Keystroke dynamics as a biometric for authentication

Keystroke dynamics as a biometric for authentication

Intrinsic generalization analysis of low dimensional representations

Facial emotion detection technology: concept, marketing applications, business drivers and challenges

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