Microsoft Technology Licensing, LLC

Magdalena Vukosavljevic

Djordje Nijemcevic

Milan Vugdelija

Ivan Stojiljkovic

Matthew Sammis Ashman

David Nister

Bodin Dresevic

Georg F Petschnigg

Wolf Kienzle

Ruchita Bhargava

Piotr Dollar

Pavle Josipović

Ana Mitrovic

Mladen Radojevic

Matthew S Ashman

A method of object detection includes receiving a first image taken from a first perspective by a first camera and receiving a second image taken from a second perspective, different from the first perspective, by a second camera. Each pixel in the first image is offset relative to a corresponding pixel in the second image by a predetermined offset distance resulting in offset first and second images. A particular pixel of the offset first image depicts a same object locus as a corresponding pixel in the offset second image only if the object locus is at an expected object-detection distance from the first and second cameras. The method includes recognizing that a target object is imaged by the particular pixel of the offset first image and the corresponding pixel of the offset second image.

Stereoscopic object detection leveraging expected object distance

A method of object detection includes receiving a first image taken by a first stereo camera, receiving a second image taken by a second stereo camera, and offsetting the first image relative to the second image by an offset distance selected such that each corresponding pixel of offset first and second images depict a same object locus if the object locus is at an assumed distance from the first and second stereo cameras. The method further includes locating a target object in the offset first and second images.

Stereoscopic object detection leveraging assumed distance

The technology described herein employs techniques for overlaying (superimposing) translated text on top of (over) scanned text in realtime. The technology recognizes text in an image and identifies a first language in which the text is written. The technology translates the text into a second language and generates an overlay in the second language. The overlay is then inserted into the display over the text in the image.

Text overlay techniques in realtime translation

Architecture that employs techniques for overlaying (superimposing) translated text on top of (over) scanned text in realtime translation to provide clear visual correlation between original text and translated text. Algorithms are provided that overlay text in cases of translated scanned text of language written in first direction to a language written in same direction, translate scanned text from a first language written in a first direction to a second language written in the opposite direction, and translated scanned text from a language written in a first direction to language written in a different direction.

Architecture that automatically computes if a quadrangular object captured in a given image is or is not a markable board (e.g., a whiteboard, green board, chalkboard, etc.). The markable board has a surface on which marks can be applied using chalk, ink, dry ink, or any other suitable marking instrument or tool for the given surface. The imaged quadrangular object can be defined as having a background image and a foreground image. The background image is representative of a markable board with no applied surface marks and the foreground image comprises all discernible marks applied to the board surface, but does not include the background image. A set of performance-friendly features is received and processed by a machine-learning classifier to compute if the given quadrangular object is a markable board. Thereafter, if the given image is determined to be a markable board, image enhancement is performed.

Automatic classification and color enhancement of a markable surface

Freeform mathematical computations are described. In implementations, an input is recognized as a freeform selection of an area of a user interface output by a computing device. Text is identified that is associated with the area defined by the freeform selection and that includes one or more numbers. A mathematical computation is performed that involves the one or more numbers.

Freeform mathematical computations

Embodiments of camera-based scanning are described. In various embodiments, one or more quadrangular objects are automatically selected from a captured image for scanning. The automatic selection is determined to be successful based on the selected quadrangular objects having an associated score that exceeds a predefined threshold. One or more scanned documents are created from portions of the captured image corresponding to the selected quadrangular objects, and the created scanned documents include corrections for perspective distortions of the selected quadrangular objects in the captured image.

Camera-based scanning

Embodiments of camera-based scanning are described. In various embodiments, scanned documents can be created using images captured by a camera associated with a device. An image captured by the camera is processed to identify portions within the image that correspond to rectangular objects such as paper, business cards, whiteboards, screens, and so forth. One or more of these portions can be selected for scanning automatically based on a scoring scheme and/or semi-automatically with the aid of input from a user. One or more scanned documents are created from the selected portions by un-warping the selected portions to remove effects of perspective (e.g., rectify the portions to rectangles) and applying various image enhancements to improve appearance.

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Bellevue, WA, United States of America

Magdalena Vukosavljevic