Fisher linear discriminant analysis (LDA) can be sensitive to the problem data. Robust Fisher LDA can systematically alleviate the sensitivity problem by explicitly incorporating a model of data uncertainty in a classification problem and optimizing for the worst-case scenario under this model. The main contribution of this paper is show that with general convex uncertainty models on the proble...

In this paper, a novel encoding scheme combining Fisher vector and bag-of-words encodings has been proposed for recognizing action in videos. The proposed Hyper-Fisher vector encoding is sum of local Fisher vectors which are computed based on the traditional Bag-of-Words (BoW) encoding. Thus, the proposed encoding is simple and yet an effective representation over the traditional Fisher Vector ...

Recently the Fisher score (or the Fisher kernel) is increasingly used as a feature extractor for classification problems. The Fisher score is a vector of parameter derivatives of loglikelihood of a probabilistic model. This paper gives a theoretical analysis about how class information is preserved in the space of the Fisher score, which turns out that the Fisher score consists of a few importa...

In this paper, a person is identified with face as a biometric feature using modified fisher face and fuzzy fisher face. The premise of this paper is to introduce modified fisher face, fuzzy fisher face and include gradual level of assignment to class being regarded as a membership grade which helps to improve recognition results. Performance of the said system is compared with traditional fish...