Edge 3 Technologies, Inc.

Honda Motor Co., Ltd.

Microsoft Technology Licensing, LLC

Golden Edge Holding Corporation

James Edward Holmes

Tarek A El Dokor

Jordan Cluster

Joshua T King

William E Glomski

Stuart Masakazu Yamamoto

Pedram Vaghefinazari

Justin R Gigliotti

Churu Yun

Matt Conway

Josh King

Graeme Asher

Maria N Ngomba

Matt McElvogue

Milind Subhash Gide

Justin R Gigliotto

Tarek El Dokor

A system and method for identifying the presence of an occupant in a vehicle. The system includes a first sensor positioned within a seating area of a seat and having a corresponding sensitive zone passing through the seating area vertically, and a second sensor positioned within a back rest area of the seat and having a corresponding sensitive zone passing through a chest area of an occupant horizontally. The first sensor is adapted to sense coarse movements adjacent to and farther from the sensor while the second sensor is adapted to capture both coarse and finer movements, such as breathing and heartbeats.

Coarse to fine movement detection in vehicles

Multiview calibration is essential for accurate three-dimensional computation. However, multiview calibration can not be accurate enough because of the tolerances required in some of the intrinsic and extrinsic parameters that are associated with the calibration process, along with fundamental imperfections that are associated with the manufacturing and assembly process itself. As a result, residual error in calibration is left over, with no known methods to mitigate such errors. Residual error mitigation is presented in this work to address the shortcomings that are associated with calibration of multiview camera systems. Residual error mitigation may be performed inline with a given calibration approach, or may be presented as a secondary processing step that is more application specific. Residual error mitigation aims at modifying the original parameters that have been estimated during an initial calibration process. These new, modified parameters are then used for triangulation and depth estimation of scene information. This approach also resolves parameter tolerances that are either too cumbersome to measure, or otherwise impossible to measure for practical stereo and multiview camera production and calibration applications.

Residual error mitigation in multiview calibration

A method and system for segmenting a plurality of images. The method comprises the steps of segmenting the image through a novel clustering technique that is, generating a composite depth map including temporally stable segments of the image as well as segments in subsequent images that have changed. These changes may be determined by determining one or more differences between the temporally stable depth map and segments included in one or more subsequent frames. Thereafter, the portions of the one or more subsequent frames that include segments including changes from their corresponding segments in the temporally stable depth map are processed and are combined with the segments from the temporally stable depth map to compute their associated disparities in one or more subsequent frames. The images may include a pair of stereo images acquired through a stereo camera system at a substantially similar time.

Method and apparatus for performing segmentation of an image

A method and system for dimensioning an object are provided. A system for dimensioning an object includes a camera associated with a dimensioning device for acquiring an image of a scene including an object to be dimensioned, and a display associated with the dimensioning device for displaying the scene acquired by the camera. A first indicator is displayed on the display indicative of a first desired position of the object to be dimensioned, and a second indicator is displayed on the display indicative of a second desired position of the object to be dimensioned. A processor is provided for receiving the scene acquired by the camera, the first indicator, and the second indicator, and for determining one or more dimensions of the object to be dimensioned.

User guided mode for measurement purposes

A user, such as the driver of a vehicle, to retrieve information related to a point of interest (POI) near the vehicle by pointing at the POI or performing some other gesture to identify the POI. Gesture recognition is performed on the gesture to generate a target region that includes the POI that the user identified. After generating the target region, information about the POI can be retrieved by querying a server-based POI service with the target region or by searching in a micromap that is stored locally. The retrieved POI information can then be provided to the user via a display and/or speaker in the vehicle. This process beneficially allows a user to rapidly identify and retrieve information about a POI near the vehicle without having to navigate a user interface by manipulating a touchscreen or physical buttons.

System and method for gesture-based point of interest search

A gesture control system includes a processor, the processor in communication with a plurality of sensors. The processor is configured to perform the steps of detecting, using the plurality of sensors, a gesture in a volume occupied by a plurality of occupants, analyzing a prior knowledge to associate the gesture with one of the plurality of occupants, and generating an output, the output being determined by the gesture and the one of the plurality of occupants.

Systems and methods for distinguishing gestures

Apparatus and method for segmenting an image

A method and system for globally updating a plurality of learning implicit gesture control systems. Embodiments can comprise receiving, by a global server and from a plurality of learning implicit gesture control systems, a user data. The global server configured to analyze the user data and determine an applicable integration level, and the global server further able to communicate with the plurality of learning implicit gesture control systems. Modifying a global parameter when the global server determines the applicable integration level is a global integration level; and transmitting the modified global parameter to the plurality of learning implicit gesture control systems.

Systems and methods for global adaptation of an implicit gesture control system

Growing community of inventors

Mesa, AZ, United States of America

James Edward Holmes