Dynamic Object Segmentation Approach For Videos

International Journal of Computer Science and Engineering
© 2020 by SSRG - IJCSE Journal
Volume 7 Issue 9
Year of Publication : 2020
Authors : Mr. Vivaram Veera Raghavulu, Prof. Dr. Ande. Prasad

How to Cite?

Mr. Vivaram Veera Raghavulu, Prof. Dr. Ande. Prasad, "Dynamic Object Segmentation Approach For Videos," SSRG International Journal of Computer Science and Engineering , vol. 7,  no. 9, pp. 18-24, 2020. Crossref, https://doi.org/10.14445/23488387/IJCSE-V7I9P104


Video analytics are analyzing video streams in real time and provide timely actionable information to make surveillance systems more predictable, accurate and efficient. Enhancing the quality of video, detecting events related to people, vehicles and enabling easy searching for video of interest. In this video analytics, image segmentation has become an indispensable task in many image and video applications.This work develops an image segmentation method based on, unsupervised dynamic object segmentation of moving and static objects occurring in a video. Objects are spatially cohesive and characterized by locally smooth motion trajectories, so they occupy regions within each frame. And, the shape and location of these regions vary slowly from frame to frame. So the existing methods don’t give the fairly good segmentation performance results within a least time. The proposed method is demonstrated to take the least computational time for achieving fairly good segmentation performance results in various image types. Thus, DOS can be formulating as tracking regions across the frames, such that the resulting tracks are locally smooth. Most prior work focuses on simplified formulation of DOS- that of motion segmentation. Typically, these methods require that the number of moving objects or layers is pre-specified.


surveillance, unsupervised, segmentation, cohesive, trajectories, region-growing, filters, stream, predictable, indispensable, frame, DOS.


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