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METHOD AND SYSTEM FOR EFFICIENTLY MINING DATASET ESSENTIALS WITH BOOTSTRAPPING STRATEGY IN 6DOF POSE ESTIMATE OF 3D OBJECTS
METHOD AND SYSTEM FOR EFFICIENTLY MINING DATASET ESSENTIALS WITH BOOTSTRAPPING STRATEGY IN 6DOF POSE ESTIMATE OF 3D OBJECTS
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机译:在3D对象的6自由度姿势估计中采用自举策略有效挖掘数据集要素的方法和系统
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摘要
A method for identifying a feature in a first image comprises establishing an initial database of image triplets, and in a pose estimation processor, training a deep learning neural network using the initial database of image triplets, calculating a pose for the first image using the deep learning neural network, comparing the calculated pose to a validation database populated with images data to identify an error case in the deep learning neural network, creating a new set of training data including a plurality of error cases identified in a plurality of input images and retraining the deep learning neural network using the new set of training data. The deep learning neural network may be iteratively retrained with a series of new training data sets. Statistical analysis is performed on a plurality of error cases to select a subset of the error cases included in the new set of training data.
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