Microsoft Technology Licensing, LLC

Kfir Karmon

Eyal Krupka

Adi Diamant

Yuval Tzairi

Daniel Freedman

Roy Varshavsky

Yagil Engel

Alon Vinnikov

Yevgeny Shapiro

Haim Somech

Benny Schlesinger

Eran Yariv

Hen Fitoussi

Daniel Sitton

Karen Master Ben-Dor

Avigad Oron

Ido Leichter

Rotem Bennet

Yoni Smolin

Aviv Hurvitz

Limor Lahiani

Ilya Gurvich

Aharon Bar-Hillel

Liat Segal

Uri Levanon

Shelly Horowitz

Noga Amit-Miller

Moti Gindi

Noam Bloom

Barak Shein

Computer implemented method for detecting a hand gesture of a user, comprising:

Detection of hand gestures using gesture language discrete values

A debugging tool comprises user input apparatus to receive user input from a debugging user, computer storage configured to hold a piece of code to be debugged, the code embodying a state machine defining a user input action, a display configured to display a timeline, and at least one processor configured to execute an iterative debugging process for visualising behaviour of the code on the timeline. The debugging process is driven by changes in the user input received at the user input apparatus and is performed so as to represent on the timeline a sequence of expected user input states of the state machine as they are actualized by the debugging user according to the permitted transitions.

Debugging tool

System for associating a computerized hand gestures model with application functions, comprising:

Hand gesture API using finite state machine and gesture language discrete values

A gesture recognition method comprises receiving at a processor from a sensor a sequence of captured signal frames for extracting hand pose information for a hand and using at least one trained predictor executed on the processor to extract hand pose information from the received signal frames. For at least one defined gesture, defined as a time sequence comprising hand poses, with each of the hand poses defined as a conjunction or disjunction of qualitative propositions relating to interest points on the hand, truth values are computed for the qualitative propositions using the hand pose information extracted from the received signal frames, and execution of the gesture is tracked, by using the truth values to determine which of the hand poses in the time sequence have already been executed and which of the hand poses in the time sequence is expected next.

Gesture recognition

An apparatus including a housing for coupling a keyboard to a tablet device through at least one respective electric interface and circuitry integrated in the housing, and a camera sensor integrated in the housing, the camera sensor positioned such that a central axis of a field of view (FOV) of the camera sensor is substantially parallel to a surface of the keyboard, the camera sensor further positioned to capture a plurality of images and to transmit the plurality of images to the tablet device through the respective electric interface and the electric circuitry. Related apparatus and methods are also described.

Accessory between display and keyboard

A system for creating hand gestures representations, comprising an interface for interacting with a user, a storage storing a plurality of discrete pose values and discrete motion values, a memory storing a gesture visual builder code, one or more processors coupled to the interface, storage and memory to execute the gesture visual builder code allowing the user to create hand gesture. The gesture visual builder code comprising code instructions to present the user with a GUI which displays a hierarchical menu driven interface, code instructions to receive iteratively user instructions from the user using the hierarchical menu driven interface, for creating a logical sequence of hand gesture by defining one or more hand pose features records and hand motion features records and code instructions to generate a code segment defining the one or more hand pose/motion features records through the discrete pose/motion values respectively.

Gestures visual builder tool

Hand gesture detection electrical device for detecting hand gestures, comprising an IC electronically integrating:

Electrical device for hand gestures detection

A system of injecting a code section to a code edited by a graphical user interface (GUI) of an integrated development environment (IDE), comprising: a memory storing a dataset associating each code segment with one hand pose feature or hand motion feature; an imager adapted to capture images of a hand while an IDE being executed on a client terminal; and processor for executing code of an application, comprising: code instructions to identify at least one of the features and at least one discrete value of the identified features from an analysis of the images; code instructions to select at least one of the code segments associated with the identified features; and code instructions to add automatically a code section generated based on the code segments and the discrete value to a code presented by a code editor of the IDE.

Translation of gesture to gesture code description using depth camera

A system for associating between a computerized model of multimodal human interaction and application functions, comprising:

Multimodal interaction using a state machine and hand gestures discrete values

Computer implemented method for computing a feature dataset classifying a pose of a human hand, comprising: Each one of the feature classifying functions outputs a current discrete pose value of an associated hand feature.

Recognition of hand poses by classification using discrete values

A movie browsing system may use a combination of long term and session based preferences to help a user browse movies using microcategories. The user preferences may be stored as microcategory weights, where the session based weights may change during a session as the system learns the types of movies a user wishes to see at that time. The long term microcategory weights may change at a slower rate than the session weights. The system may present a diverse set of microcategories to a user in an effort to diverge the search and learn the user's current interest, and may refine the weights as the user browses to converge to a desired movie. A user interface may operate on a television screen with a minimum of user input controls to navigate the browsing system while still collecting user preferences.

Movie discovery system

A scraping mechanism may download a web page from a retailer and extract information for each item being offered for sale. The scraping mechanism may parse the published HTML code to identify items for sale, along with other parameters that may be presented in the web page. From the web page, a data structure may be created that represents the items for sale, and the data structure may be used to generate advertisements for the retailer, add the items to a search engine, or for other uses. In some embodiments, the retailer may include hints, tags, or other annotations in the HTML code to facilitate the data capture. The web page may be a standard public page or may be a private page accessible to the scraping mechanism only.

Semantic tagged ads

Messages to a focal user are organized by relevance of the message originators. A visual representation of the messages includes a focal user representation (textual or graphic) and multiple contact representations (textual or graphic). The contact representations are displayed at respective relevance distances from the focal user representation. Text regions present the contents of messages from the source contacts, e.g., using graphic novel-style word balloons. The contact representations can be positioned on screen in maps, radar format, or other configurations. Users can filter contacts according to relevance, and can filter messages by pertinence.

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Petach-Tikva, Israel

Kfir Karmon