Patología asociada al consumo de tabaco 1 Patología respiratoria 82-

The rise in the popularity of RGB-D cameras in recent years has created a demand for good RGB-D feature points. Existing RGB feature points do work with RGB-D images, but interest points selected in RGB images tend to be near corners and edges where there is a sharp discontinuity in depth resulting in a decrease in the quality of the depth measurement. Feature detectors and descriptors that leverage the available depth data should be able to identify more distinct locations in the scene that can be found more consistently. Such detectors would greatly improve the range image sampling process prior to pairwise alignment. Descriptor extractors that consider the surface normal near an interest point and adjust the sampling pattern ac- cordingly would produce descriptors that are much more robust to changes in perspective. Better descriptors would reduce the number of match outliers, allowing for a faster and more accurate RANSAC based visual odometry estimate.

The update rules for the Adjustable BRISK-AGAST detector could also be improved. Smarter update rules inspired by a model of the relationship be- tween the threshold value, image characteristics, and the number of features would be more responsive and better able to regulate the feature count.

Along the same lines, a self-tuning SURF detector would be of great benefit to the RGB-D SLAM System. Such a detector would produce detection results comparable to the current implementation while halving detection times.

The map distortion application could be improved by a more informed method of sampling the map. Under certain transformations and poses, the map sampling algorithm was unable to provide enough diversity in the keyframes, resulting in grainy looking images. Incorporating the affine trans- formation used to distort the map into the keyframe sampling process would help identify locations where sampled map is sparse and chose keyframes accordingly, improving sample diversity and image quality.

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