Videosurf, Inc.

Microsoft Technology Licensing, LLC

Fringefy Ltd.

Eitan Sharon

Eran Borenstein

Achiezer Brandt

Mehmet Nejat Tek

Asael Moshe

Achi Brandt

Lior Delgo

Jason White

Simon John Baker

Enrique De La Garza

Richard D Prologo

David Alles

Saleel Sathe

Sunaad Nataraju

Praveen Kumar Vemparala

Michael G Lucero

Virginia M Musante

Stav Yagev

Mehmet Tek

Praveen Srinivasan

Assif Ziv

Omer Meir

A system and method are disclosed for quickly and easily browsing to points of interest within a recorded video. In examples, the present system works in tandem with a segment list which includes a list of different video sequences of a stored video of an event. One typical example of a segment list is a play-by-play (PBP) which is prepared contemporaneously with a sporting event. Segments from a segment list may be associated with, or indexed to, corresponding sequences from the stored video. Thereafter, a user interface allows a user to interactively watch or browse the event by jumping to a desired point in the video for playback by selecting its associated segment from the user interface.

Browsing videos via a segment list

An image abstraction engine is provided to characterize scenes like typically found in an urban setting. Specifically buildings and manmade structures have certain characteristic properties that may be abstracted and compressed in a manner that takes advantage of those characteristic properties. This allows for a more compact and computationally efficient abstraction and recognition.

Image abstraction system

A video visual and audio query system for quickly identifying video within a large known corpus of videos being played on any screen or display. In one embodiment, the system can record via a mobile phone camera and microphone a live video clip from the TV and transcode it into a sequence of frame-signatures. The signatures representative of the clips can then be matched against the signatures of the TV content in a corpus across a network to identify the correct TV show or movie.

Video visual and audio query

An automated content recognition system accurately and reliably generates content identification information for multimedia content without accessing the multimedia content or a reliable source of the multimedia content. The system receives content-based queries having fingerprints of multimedia content. The system compares the individual queries to one another to match queries and thereby form query clusters that correspond to the same multimedia content. The system aggregates identification information from the queries in a cluster to generate reliable content identification information from otherwise unreliable identification information.

Automated multimedia content recognition

Technology described herein provides techniques for screen detection. This could be a dynamic screen, such as a display screen of an electronic device, or a static screen such as a street sign. In one aspect, a screen is detected in frames of image data. An active image and/or an average color image may be formed based on frames of image data. A set of lines that are candidate for boundaries of a screen are identified in the frames. The active image and/or an average color is integrated on both sides of each line in the set of lines to form integration results. A set of screen candidates are formed based on the integration results. Screens in the screen candidates are scored according to a criterion. One or top few of the screens in the set of screen candidates is selected based on the scoring.

Screen detector

Techniques for aligning images are disclosed. The frames might have been captured by a video camera on a hand held device, as one example. Collaboratively aligning related frames of image data is taught. Collaborative alignment determines a correspondence between pixels in pairs of the frames of image data, as well as a confidence in that correspondence. A coordinate system (or transformation) is assigned to each of the frames that is consistent with the correspondences between each of the frame pairs. The confidence in the respective correspondences may be used to provide a weighting to a correspondence when assigning the coordinate systems. Outlying frames may be discarded, and the process repeated for a robust solution.

Collaborative alignment of images

A method analyzes the visual content of media such as videos for collecting together visually-similar appearances in their constituent images (e.g. same scenes, same objects, faces of the same people.) As a result, the most relevant and salient (of clearest and largest presence) visual appearances depicted in the videos are presented to the user, both for the sake of summarizing the video content for the users to 'see before they watch' (that is, judge by the depicted video content in a filmstrip-like summary whether they want to mouse-click on the video and actually spend time watching it), as well as for allowing to users to further refine their video search result set according to the most relevant and salient video content returned (e.g. largest screen-time faces).

Apparatus and software system for and method of performing a visual-relevance-rank subsequent search

This document describes techniques and apparatuses enabling brand detection in audiovisual media. The techniques detect a brand exposed within audiovisual media, such as a name or logo for a product or service, and based on this brand, present a brand advertisement or enable selection of an interactive experience that is associated with the brand. By so doing, marketers enable viewers to quickly and easily learn more about the product or service.

Brand detection in audiovisual media

Systems and methods for identifying and searching video are disclosed. A video search and identification system includes a catalog representing relationships between video, data and/or objects to enable querying and search based on visual representations of video as well as data or other information associated with the video. In one example, the catalog includes video nodes, metadata nodes and card nodes, although additional or fewer node types may be used. A visual-based video identification system is provided to identify content in video sources. An unidentified video source is accessed and visual fingerprints of one or more frames are generated as query signatures for matching against a base set of known signatures. Confidence measures are generated at the bit level to assist in query signature processing.

Video identification and search

A computer program and apparatus function to extract objects from a video by identifying regions to be tracked, tracking the regions across several frames, calculating motions of the regions, and identifying new regions to be tracked. Regions of a selected frame of the video that are appropriate for tracking are selected. Tracking of the identified regions is then performed across frames subsequent to the selected frame of the video. Motions of the identified regions are calculated, and new regions for tracking are identified.

Computer program and apparatus for motion-based object extraction and tracking in video

A method of extracting objects from a video includes the identification of regions to be tracked, tracking the regions across several frames, calculating motions of the regions, and identifying new regions to be tracked. Regions of a selected frame of the video that are appropriate for tracking are selected. Tracking of the identified regions is then performed across frames subsequent to the selected frame of the video. Motions of the identified regions are calculated, and new regions for tracking are identified.

Growing community of inventors

San Mateo, CA, United States of America

Eitan Sharon