Object recognition from local scale-invariant features
Citations
143Â citations
Cites background from "Object recognition from local scale..."
...Therefore, the complex local descriptors, such as SIFT [7], might be suitable to characterize the image features around each point along the boundaries of lung fields....
[...]
...SIFT, as detailed in [7], consists of four major steps: (1) scale-space peak selection; (2) key point localization; (3) orientation assignment; (4) key point description....
[...]
143Â citations
Cites background from "Object recognition from local scale..."
...Apart from denoising, other algorithms that can benefit from noise level estimates include motion estimation [25], super-resolution [26], shapefrom-shading [27], and feature extraction [28]....
[...]
143Â citations
142Â citations
142Â citations
Cites background or methods from "Object recognition from local scale..."
...In the last decades, many efforts have been made to develop feature representations that can provide useful low-level information from images (e.g., [1, 2])....
[...]
...To address this difficulty, we show the connections between mixture models and RBMs and present an efficient training method for RBMs that utilize these connections....
[...]
References
[...]
5,672Â citations
4,310Â citations
2,037Â citations
1,756Â citations
"Object recognition from local scale..." refers background or methods in this paper
...This allows for the use of more distinctive image descriptors than the rotation-invariant ones used by Schmid and Mohr, and the descriptor is further modified to improve its stability to changes in affine projection and illumination....
[...]
...For the object recognition problem, Schmid & Mohr [19] also used the Harris corner detector to identify interest points, and then created a local image descriptor at each interest point from an orientation-invariant vector of derivative-of-Gaussian image measurements....
[...]
..., Schmid & Mohr [19]) has shown that efficient recognition can often be achieved by using local image descriptors sampled at a large number of repeatable locations....
[...]
...However, recent research on the use of dense local features (e.g., Schmid & Mohr [19]) has shown that efficient recognition can often be achieved by using local image descriptors sampled at a large number of repeatable locations....
[...]
1,574Â citations
"Object recognition from local scale..." refers methods in this paper
...[23] used the Harris corner detector to identify feature locations for epipolar alignment of images taken from differing viewpoints....
[...]