Hybrid Method for Moving Object Exploration in Video Surveillance

Moving object in a video could be explored using hybrid methodologies as one among the enticing field of vision in computers. It is extensively applied in video surveillances and target identification system. Extracting reliable information accurately is a rigorous task in a challenging environment. This paper investigates the problem of detecting an object in dynamic scenes. We suggest two method 1) feature extraction using FBF 2) Image matching using ISURF. The ISURF (Improved Speeded up Robust Feature detection) is the improvised method of original SURF algorithm. In this the matching duration is reduced by limiting the total number of features to be compared. The FBF (Fast Bilateral Filtering) algorithm is suggested for feature extraction and denoising the captured key frames. Thus this paper proposes a hybrid method for moving object exploration in a dynamic scene with reduced time.

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