Radoslaw Weychan

Influence of low resolution of images on reliability of face detection and recognition

In this paper we analyze reliability of the real-time system for face detection and recognition from low-resolution images, e.g., from video monitoring images. First, we briefly describe main features of the standards for biometric face images. Available scientific databases have been checked for compliance with these biometric standards. During the research we have considered both the correctness of extraction (location) of the face from the image as well as the correctness of the identification (based on the eigenfaces approach). To the tests we have used the face databases that allow to study tolerance to illumination and face positions. We have compared various face detection techniques and analyzed minimum requirements for the resolution of facial images. Finally, an influence of the resolution reduction on the FAR/FRR of the recognition is presented.

Face Recognition from Low Resolution Images

This paper describes an analysis of the real-time system for face recognition from video monitoring images. First, we briefly describe main features of the standards for biometric face images. Available scientific databases have been checked for compliance with these biometric standards. Next, we concentrate on the analysis of the prepared face recognition application based on the eigenface approach. Finally, results of our face recognition experiments with images of reduced resolution are presented. It turned out that the proposed and tested algorithm is quite resistant to changing the resolution. The recognition results are acceptable even for low-resolution images (16×20 pixels).

Implementation aspects of speaker recognition using Python language and Raspberry Pi platform

The paper presents implementation aspects of real time speaker recognition from Internet radio broadcasts. The proposed solution is based on the free and open source Python development tools. The prepared software was tested with the Windows environment and then adapted to the Unix operating system running on the Raspberry Pi platform. We show what libraries are most convenient in order to implement individual blocks of the speaker recognition algorithm. In the paper we also indicate parameters, for which the algorithm exhibits the greatest efficiency. The prepared software is available on the Github file repository.

Multithreaded Java approach to speaker recognition

In this paper an analysis of multithread approach to speaker recognition is presented. Two cases have been investigated — the use of multithreading first, to reduce the total time of training and testing (when processing the speaker database) and second, to reduce the time of a single speaker recognition (e.g. in voice-based access systems). We have investigated the processing time in function of a number of threads in order to find the optimal number for 8-core CPU. The obtained results show that the computation time can be reduced even over 5 times for this kind of processor. The prepared implementation is available on Github source code repository.

Real Time Recognition Of Speakers From Internet Audio Stream

Abstract In this paper we present an automatic speaker recognition technique with the use of the Internet radio lossy (encoded) speech signal streams. We show an influence of the audio encoder (e.g., bitrate) on the speaker model quality. The model of each speaker was calculated with the use of the Gaussian mixture model (GMM) approach. Both the speaker recognition and the further analysis were realized with the use of short utterances to facilitate real time processing. The neighborhoods of the speaker models were analyzed with the use of the ISOMAP algorithm. The experiments were based on four 1-hour public debates with 7–8 speakers (including the moderator), acquired from the Polish radio Internet services. The presented software was developed with the MATLAB environment.