A Fire Fly Optimization Based Video Object Co-Segmentation

Abstract- Video object co-segmentation is a method of segmenting and discovering primary object from multiple videos without human annotation. In this paper, we are presenting a firefly based video object co-segmentation method. Here we are using SIFT flow method for object segmentation and firefly algorithm for object optimization. SIFT flow descriptor discovers the corresponding object using inter-frame motion flow from optical flow. But it will not capture the optimal motion of inter-frame. So we are using Firefly approach in addition to SIFT flow. Firefly approach captures optimal inter-frame motion based on the velocity updation and position of the particle for better results.  SIFT flow produces segmented primary objects over the entire video data set. Finally we combine this segmented object to get high quality original videos. The results that we obtained from conducting the experiment show that the Firefly based co-segmentation method achieves high accuracy compared with the existing co-segmentation method.

Keywords— Video object co-segmentation, energy optimization, object refinement, spatio-temporal scale-invariant feature transform (SIFT) flow.

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