Event detection using local binary pattern based dynamic textures

Detecting suspicious events from video surveillance cameras has been an important task recently. Many trajectory based descriptors were developed, such as to detect people running or moving in opposite direction. However, these trajectory based descriptors are not working well in the crowd environments like airports, rail stations, because those descriptors assume perfect motion/object segmentation. In this paper, we present an event detection method using dynamic texture descriptor. The dynamic texture descriptor is an extension of the local binary patterns. The image sequences are divided into regions. A flow is formed based on the similarity of the dynamic texture descriptors on the regions. We used real dataset for experiments. The results are promising.