Interest point detection is the vital aspect of computer vision and image processing. Interest point detection is very important for image retrieval and object categorization systems from which local descriptors are calculated for image matching schemes. Earlier approaches largely ignored color aspect as interest point calculation are largely based on luminance. However the use of color increas...

In this paper we propose a novel method for continuous visual event recognition (CVER) on a large scale video dataset using max-margin Hough transformation framework. Due to high scalability, diverse real environmental state and wide scene variability direct application of action recognition/detection methods such as spatio-temporal interest point (STIP)-local feature based technique, on the wh...

5 We investigate how human action recognition can be improved by considering spatio-temporal layout of 6 actions. From literature, we adopt a pipeline consisting of STIP features, a random forest to quantize the 7 features into histograms, and an SVM classifier. Our goal is to detect 48 human actions, ranging from simple 8 actions such as walk to complex actions such as exchange. Our contributi...

Video based action recognition has been an active area of research in recent years. This is due to the many potential applications such as video surveillance, video content analysis, human computer interaction and video archiving. The ongoing trend of research deals with many complex action recognition problems such as appearance, pose and illumination variations but problem video quality is st...

MIRJANA POPOVSKA1, VERA RADOJKOVA-NIKOLOVSKA1, ANA MINOVSKA2*, DORIANA AGOP FORNA3, ILIJANA MURATOVSKA1, NORINA CONSUELA FORNA4 1 St. Cyril and Methodius University, Faculty of Dentistry, Department of Oral Pathology and Periodontology, 17 Vodnjanska St. 1000 Skopje, Republic of Macedonia 2 University “Gotse Delchev” of Shtip, Faculty of Medical Sciences, Department of Studies of Dental Medicin...