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Andrew C. Gallagher

Researcher at Google

Publications -  253
Citations -  9013

Andrew C. Gallagher is an academic researcher from Google. The author has contributed to research in topics: Digital image & Pixel. The author has an hindex of 51, co-authored 250 publications receiving 8616 citations. Previous affiliations of Andrew C. Gallagher include Eastman Kodak Company & OmniVision Technologies.

Papers
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Journal ArticleDOI

3D Reasoning from Blocks to Stability

TL;DR: This paper proposes a new algorithm to parse a single RGB-D image with 3D block units while jointly reasoning about the segments, volumes, supporting relationships, and object stability, and designs an energy function for representing the quality of the block representation based on these properties.
Patent

Classifying image regions based on picture location

TL;DR: A method of classifying regions in a digital image or video captured by an image capture device includes providing a geographic location determining device associated with the image capture devices, using the location determining devices to measure the image-capture location at substantially the time that the digital image and video was captured as mentioned in this paper.
Proceedings ArticleDOI

Semi-automatic assembly of real cross-cut shredded documents

TL;DR: A semi-automatic approach for cross-cut shredded document reassembly with automatic algorithms proposed for segmenting and orienting individual shreds from a scanned shred image, as well as for computing features and ranking potential matches for each shred.
Patent

Multiple lens camera providing a range map

TL;DR: In this article, an electronic camera for producing an output image of a scene from a captured image signal includes a first imaging stage comprising a first image sensor for generating a first sensor output and a first lens for forming a first images of the scene on the first sensor, and a second imaging stage consisting of a second image sensor, where the lenses have different focal lengths.
Patent

Estimating aesthetic quality of digital images

TL;DR: In this article, a method for estimating the aesthetic quality of an input digital image comprising using a digital image processor for performing the following: determining one or more vanishing points associated with the input digital images by automatically analyzing the digital image; computing a compositional model from at least the positions of the vanishing point(s); and producing an aesthetic quality parameter for the image responsive to the model.