Using computer vision in security applications

In this paper we present projects developed in the Computer Vision Laboratory, which address the issue of safety. First, we present the Internet Video Server (IVS) monitoring system [5] that sends live video stream over the Internet and enables remote camera control. Its extension GlobalView [1,6], which incorporates intuitive user interface for remote camera control, is based on panoramic image. Then we describe our method for automatic face detection [3] based on color segmentation and feature extraction. Finally, we introduce our SecurityAgent system [4] for automatic surveillance of observed location

The 'not-so-strange' body in the mirror: : A principal components analysis of direct and mirror self-observation

This document is the Accepted Manuscript version of the following article: Paul M. Jenkinson, and Catherine Preston, ‘The “not-so-strange” body in the mirror: A principal components analysis of direct and mirror self-observation’, Consciousness and Cognition, Vol. 48, pp. 262-272, first published online 4 January 2017, doi: http://dx.doi.org/10.1016/j.concog.2016.12.007 This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/.In this study we adopted a psychometric approach to examine how the body is subjectively experienced in a mirror. One hundred and twenty-four healthy participants viewed their body for five minutes directly or via a mirror, and then completed a 20-item questionnaire designed to capture subjective experiences of the body. PCA revealed a two-component structure for both direct and mirror conditions, comprising body evaluations (and alienation) and unusual feelings and perceptions. The relationship between these components and pre-existing tendencies for appearance anxiety, body dysmorphic-type beliefs, dissociative symptomatology, self-objectification and delusion ideation further supported the similarity between direct and mirror conditions; however, the occurrence of strange experiences like those reported to occur during prolonged face viewing was not confirmed. These results suggest that, despite obvious differences in visual feedback, observing the body via a mirror (as an outside observer) is subjectively equivalent to observing the body directly (from our own viewpoint).Peer reviewedFinal Accepted Versio

Virtual samples construction using image-block-stretching for face recognition

© Springer International Publishing AG 2016. Face recognition encounters the problem that multiple samples of the same object may be very different owing to the deformation of appearances. To synthesizing reasonable virtual samples is a good way to solve it. In this paper, we introduce the idea of image-block-stretching to generate virtual images for deformable faces. It allows the neighbored image blocks to be stretching randomly to reflect possible variations of the appearance of faces. We demonstrate that virtual images obtained using image-block-stretching and original images are complementary in representing faces. Extensive classification experiments on face databases show that the proposed virtual image scheme is very competent and can be combined with a number of classifiers, such as the sparse representation classification, to achieve surprising accuracy improvement

Speech Processing in Computer Vision Applications

Deep learning has been recently proven to be a viable asset in determining features in the field of Speech Analysis. Deep learning methods like Convolutional Neural Networks facilitate the expansion of specific feature information in waveforms, allowing networks to create more feature dense representations of data. Our work attempts to address the problem of re-creating a face given a speaker\u27s voice and speaker identification using deep learning methods. In this work, we first review the fundamental background in speech processing and its related applications. Then we introduce novel deep learning-based methods to speech feature analysis. Finally, we will present our deep learning approaches to speaker identification and speech to face synthesis. The presented method can convert a speaker audio sample to an image of their predicted face. This framework is composed of several chained together networks, each with an essential step in the conversion process. These include Audio embedding, encoding, and face generation networks, respectively. Our experiments show that certain features can map to the face and that with a speaker\u27s voice, DNNs can create their face and that a GUI could be used in conjunction to display a speaker recognition network\u27s data

Theories of understanding others: the need for a new account and the guiding role of the person model theory

What would be an adequate theory of social understanding? In the last decade, the philosophical debate has focused on Theory Theory, Simulation Theory and Interaction Theory as the three possible candidates. In the following, we look carefully at each of these and describe its main advantages and disadvantages. Based on this critical analysis, we formulate the need for a new account of social understanding. We propose the Person Model Theory as an independent new account which has greater explanatory power compared to the existing theorie