Query Object Detection in Big Video Data on Hadoop Framework

In the emerging era of technology filled with multimedia sources video lecturing is becoming increasingly significant. The detection of objects in such systems is crucial for application areas such as identification of person, gender, event and other non-living things. This paper throws some light on adopting the methods to handle such Big video data using Hadoop framework. Hadoop Map-Reduce technology in assistance with the video processing algorithms refined till a certain efficiency helps in detecting the objects in Big video data. The Big video data is initially distributed to various nodes of Hadoop environment where in each node functions in processing of videos. The cull mapper distributes videos to all nodes in a cluster. In the first map phase original videos are converted from RGB to gray scale since processing on gray scale videos is three times faster than that of processing on RGB videos. Then in second map phase, the background subtraction method for object detection is carried out. The detected object can be then classified into its category.