Development of facial recognition or expression recognition algorithms requires input data to thoroughly test the performance of algorithms in various conditions. Researchers are developing various methods to face challenges like illumination, pose and expression changes, as well as facial disguises. In this paper, we propose and establish a dataset of thermal facial images, which contains a set of neutral images in various poses as well as a set of facial images with different posed expressions collected with a thermal infrared camera. Since the properties of face in the thermal domain strongly depend on time, in order to show the impact of aging, collection of the dataset has been repeated and a corresponding set of data is provided. The paper describes the measurement methodology and database structure. We present baseline results of processing using state-of-the-art facial descriptors combined with distance metrics for thermal face reidentification. Three selected local descriptors, a histogram of oriented gradients, local binary patterns and local derivative patterns are used for elementary assessment of the database. The dataset offers a wide range of capabilities – from thermal face recognition to thermal expression recognition.
Autonomic nervous system of the pelvis is still poorly understood. Every year more and more pelvic procedures are carried out on patients suff ering from diff erent pelvic disorders what leads to numerous pelvic dysfunctions. Authors tried to review, starting from historical and clinical background, the most important reports on anatomy of the pelvic autonomic plexuses. We also pay attention to complete lack of knowledge of students of medicine on the autonomic nervous structures in the area studied. We present anatomical description of the pelvic plexuses including their visceral branches and anatomy of surrounding pelvic tissues which still remains unclear. More and more attention is paid to the topography of the plexuses specially because of new pain releasing techniques — neurolysies.