Adaptive Real-time Object Recognition for Augmented Reality
نویسندگان
چکیده
One of the key features of virtually all object recognition systems is the ability do deal with occlusions of detected objects. This article is focused on identification of occluded artificial objects such as square markers. The article reviews frequently used methods for detection of partially occluded markers. Further, our implementation of two object recognition methods is presented. The first method is based on morphological operations. The other one is based on a SURF feature extraction and matching. Finally, our adaptive detection method that takes the best from both implementations is described. Presented method is especially useful for real-time applications such as augmented reality systems.
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