Wisconsin Alumni Research Foundation

Adobe, Inc.

Brandon M Smith

Mohit Gupta

Zhe Lin

Jonathan Worthen Brandt

Sizhuo Ma

Pratham H Desai

Vishal R Agarwal

In accordance with some embodiments, systems, methods and media for determining object motion in three dimensions using light field image data are provided. In some embodiments, a system for three dimensional motion estimation is provided, comprising: an image sensor; optics that create many images of a scene; and a hardware processor configured to: cause the image sensor to capture a first plurality of images; generate a first light field; cause the image sensor to capture a second plurality of images at a second time; generate a second light field; calculate light field gradients using the first light field and second light field; and calculate, for each point in the scene, three dimensional motion using the light field gradients by applying a constraint to the motion in the scene.

Systems, methods, and media for determining object motion in three dimensions from light field image data

In accordance with some embodiments, systems, methods and media for determining object motion in three dimensions using speckle images are provided. In some embodiments, a system for three dimensional motion estimation is provided, comprising: a light source; an image sensor; and a hardware processor programmed to: cause the light source to emit light toward the scene; cause the image sensor to capture a first defocused speckle image of the scene at a first time and capture a second defocused speckle image of the scene at a second time; generate a first scaled version of the first defocused image; generate a second scaled version of the first defocused image; compare each of the first defocused image, the first scaled version, and the second scaled version to the second defocused image; and determine axial and lateral motion of the object based on the comparisons.

Systems, methods and, media for determining object motion in three dimensions using speckle images

In an example embodiment, for each of the image exemplars, a first location offset between an actual landmark location for a first landmark in the image exemplar and a predicted landmark location for the first landmark in the image exemplar is determined. Then, a probability that the image recognition process applied using the first feature produces an accurate identification of the first landmark in the image exemplars is determined based on the first location offsets for each of the image exemplars. A weight may then be assigned to the first feature based on the derived probability. An image recognition process may then be performed on an image, the image recognition process utilizing a voting process, for each of one or more features, for one or more landmarks in the plurality of image exemplars, the voting process for the first feature weighted according to the weight assigned to the first feature.

Exemplar-based feature weighting

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Madison, WI, United States of America

Brandon M Smith