This paper utilizes the intra-difference in still images to segment a face from its background and then combines the intra-difference detection result with the eigenface/eigenfeature methods to identify the face. This novel diverse scheme can finally solve the problem of accuracy in practical applications, thus broadening the application of face recognition into more versatile situations such a...

With the proliferation of inexpensive video surveillance and face recognition technologies, it is increasingly possible to track and match people as they move through public spaces. To protect the privacy of subjects visible in video sequences, prior research suggests using ad hoc obfuscation methods, such as blurring or pixelation of the face. However, there has been little investigation into ...

We show that a simple, memory-based technique for appearance-based face recognition, motivated by the realworld task of visitor identification, can outperform more sophisticated algorithms that use Principal Components Analysis (PCA) and neural networks. This technique is closely related to correlation templates; however, we show that the use of novel similarity measures greatly improves perfor...

It is still challenging to recognize faces reliably in videos from mobile camera, although mature automatic face recognition technology for still images has been available for quite some time. Suppose we want to be alerted when suspects appear in the recording of a police BodyCam, even a good face matcher on still images would give many false alarms due to the uncontrolled conditions. This pape...

The recent growth in CCTV systems and the challenges of automatically identifying humans under the adverse visual conditions of surveillance have increased the interest in soft biometrics, which are physical attributes that can be used to describe people semantically. Soft biometrics enable human identification based on verbal descriptions, and they can be captured in conditions where it is imp...

We propose a novel approach to face identification and verification based on the Error Correcting Output Coding (ECOC) classifier design concept. In the training phase the client set is repeatedly divided into two ECOC specified sub-sets (super-classes) to train a set of binary classifiers. The output of the classifiers defines the ECOC feature space, in which it is easier to separate transform...

In this work, we propose to divide each class (a person) into subclasses using spatial partition trees which helps in better capturing the intra-personal variances arising from the appearances of the same individual. We perform a comprehensive analysis on within-class and within-subclass eigenspec-trums of face images and propose a novel method of eigen-spectrum modeling which extracts discrimi...