Learning good features for visual odometry

A computer program product for pose estimation, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising:

• receiving, by a processor, a plurality of images from one or more cameras;
• generating, by the processor with a feature extraction convolutional neural network (CNN), a feature map for each of the plurality of images;
• estimating, by the processor with a feature weighting network, a score map from a pair of the feature maps;
• predicting, by the processor with a pose estimation CNN, a pose from the score map and a combined feature map;
• and
• controlling an operation of a processor-based machine to change a state of the processor-based machine, responsive to the pose.

A pose estimation system, the pose estimation system comprising:

• a processing system including a processor and memory coupled to the processor, the processing system programmed to:
• receive a plurality of images from one or more cameras;
• generate, with a feature extraction convolutional neural network (CNN), a feature map for each of the plurality of images;
• estimate, with a feature weighting network, a score map from a pair of the feature maps;
• predict, with a pose estimation CNN, a pose from the score map and a combined feature map;
• and
• control an operation of a processor-based machine to change a state of the processor-based machine, responsive to the pose.