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Multi-Object Tracking Based on Hybrid Kalman/H∞ Filtering

Adinarayana Ekkurthi Ekkurthi, Dr.G. Sudhavani


In this paper, we utilize the hybrid H-infinity and Kalman filtering for multiple object tracking in the video arrangements. Here, the proposed system will be the joined execution of Kalman filter and the H-infinity filter. The Kalman filter, known as the optimal linear quadratic estimator, it is a profoundly productive filter and it broadly utilized as a part of tracking frameworks. The H∞ filter is a recursive algorithm, just the last time step and current state estimation are required for object tracking yet no history perception is required. Consequently, there would be no necessity for a high limit of computational stockpiling. At first, the color spatial feature, texture feature and the edge gradient features are removed from the targeted object to figure the matching degree between the Candidate feature and the object feature. At that point the joined H-infinity and the Kalman filter approach is planned to find the certifiable location of the objects and additionally assess the speed of that object in light of the fact that the objects are moved by certain motion law (position and velocity). The Kalman filter doesn't limit the mean square error. In this way, the H-infinity filter limits the mean square error and also utilized to limit the impact of unexpected noise whose insights are obscure. Usage of the proposed model and the techniques were completed in MATLAB and the execution of the proposed strategy has better execution and precision.


Multi-object tracking; Background subtraction; Histogram equalization; Multi feature fusion; Hybrid Kalman and H-infinity filter.

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