Development of a fast panoramic face mosaicking and recognition system

Abstract

We present some development results on a system that performs mosaicking of panoramic faces. Our objective is to study the feasibility of panoramic face construction in real time. To do so, we built a simple acquisition system composed of five standard cameras, which together can take simultaneously five views of a face at different angles. Then, we chose an easily hardware-achievable algorithm, consisting of successive linear transformations, in order to compose a panoramic face from these five views. The method has been tested on a large number of faces. In order to validate our system, we also conducted a preliminary study on panoramic face recognition, based on the principal-component method. Experimental results show the feasibility and viability of our system. This allows us to envisage later a hardware implementation. We also are considering using our system for other applications, such as human expression categorization and fast 3-D face reconstruction.

Prospects of Biometrics at-a-Distance

“…The complexity of biometric identification is reduced by using multiple cameras followed by fast linear transformations of the images (Yang et al, 2005). Real-time applications can benefit from this due to the low amount of processing required to create an image (Yang et al, 2005).…”

“…The creation of facial recognition images can be done through the construction of mosaicked panoramic images which consist of pieces of 2-D pictures put together to get a full 3-D facial image (Yang et al, 2005). The complexity of biometric identification is reduced by using multiple cameras followed by fast linear transformations of the images (Yang et al, 2005).…”

“…Principal-component analysis (PCA) is an adaptable approach to facial recognition that provides the user flexibility when dealing with an image of poor quality (Yang et al, 2005). It uses statistical procedure to correlate variables into sets of linearly uncorrelated variables called principal components (Wikipedia, 2015).…”

An Evaluation of Bimodal Recognition Systems Based on Voice and Facial Images

“…Finally, as it can be seen in the equation (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21), the idea is to estimate the joint density functions of all matchers for each class and then apply the Neyman- 2) Directly estimate the joint density functions of the scores of all matchers that pertain to a given class (i.e. ( 1, … , | )).…”

“…In [21] the authors followed a similar method to perform mosaicking of five views of a face at different angles to create a panoramic face construction in real time. Another typical application of sensor level fusion is the mosaicking of various partial fingerprints impressions of a person in order to create a better fingerprint image.…”