Video Objects Detection Using Spatial and Temporal Segmentation
Abstract: Moving object detection and tracking in a Video sequence is a crucial task in many computer vision and image analysis applications such as video surveillance, event detection, activity recognition etc. I here proposed a new method for detecting video objects. This method includes two schemes. These are Spatio-temporal spatial segmentation and temporal segmentation. Combinations of these two schemes are used to detect the moving objects. Both single and multiple objects could be detected through this scheme. Here Markov Random Field (MRF) model is used to represent image. It can be used to model spatial constraints such as smoothness of image regions, spatial regularity of textures and depth continuity in stereo construction.
Keywords: Image segmentation, edge detection, Markov random field, Change detection mask, Maximum a posteriori probability
How to Cite?: Hima E P, "Video Objects Detection Using Spatial and Temporal Segmentation", Volume 2 Issue 7, July 2013, International Journal of Science and Research (IJSR), Pages: 255-258, https://www.ijsr.net/getabstract.php?paperid=02013137, DOI: https://dx.doi.org/10.21275/02013137