Anmin Zhu and Yanming Chen
Object detection, random ferns, machine learning
A machine-learning-based algorithm for detecting a moving object is proposed in this paper. It is composed of an object-detection model, and a machine-learning model. The object-detection model is used to detect the object by applying the random ferns method, while the machine-learning model is used to maintain the object expression in the object detecting model by online learning. Using the proposed algorithm, a moving object can be detected in real-time environment with robustness, such as illumination change, high-speed motion, object occlusion, object distortion, and noisy object. The effectiveness and the efficiency of the proposed algorithm are demonstrated by experiments in comparison with other models.
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