Hewlett-packard Development Company, L.p.

Delta Design, Inc.

Yun David Tang

Daniel R Tretter

David Bradley Short

Jinman Kang

Kar-Han Tan

Vijaykumar Nayak

Amit A Marathe

Hao Meng

Otto Kenneth Sievert

Jian Fan

Su Wang

Santiago Garcia-Reyero Vinas

Kexiang Ken Ding

Guoxing Yang

Kar Han Tan

Luis A Muller

Roya Susan Akhavain

Divya Sharma

Peter Siyuan Zhang

James Frandsen

Xiangfei Qian

Brian R Jung

Michel Mabene

Examples of electronic devices are described herein. In some examples, an electronic device includes a camera to capture a composite image comprising multiple images of a location. In some examples, the electronic device includes a processor to crop a portion of the composite image based on a field-of-view of the camera. In some examples, the processor is to determine whether a neural network identifies the cropped portion. In some examples, the processor is to generate a unique identifier (ID) for the cropped portion in response to the cropped portion being unidentified by the neural network. In some examples, the processor is to associate the unique ID of the cropped portion with the location.

Location identification with multiple images

A method of determining a region of interest may include with a first image capturing device, determining a region of interest within a field of view common between the first image capturing device and a second image capturing device, the first image capturing device capturing an image at a lower resolution than the second image capturing device; determining a corner defining the region of interest; and upscaling the determined corner to match a corner within a field of view of an image captured by the second image capturing device.

Dual camera regions of interest display

A multiple-pattern fiducial for a heterogeneous imaging sensor system. The multiple-pattern fiducial includes a first pattern detectable by a first wavelength of electromagnetic energy, and a second pattern detectable by a second wavelength of electromagnetic energy.

Multiple-pattern fiducial for heterogeneous imaging sensor systems

An example system includes a pose engine to determine a pose of a camera based on an environmental measurement. The system also includes a transform engine to determine a transform to apply to frames captured by the camera based on the pose of the camera. The system includes a correction engine to apply the transform to the frames captured by the camera in substantially real-time with capturing of the frames.

Substantially real-time correction of perspective distortion

Examples disclosed herein relate to detecting misalignment of a touch sensitive mat. Examples include detecting corners of the touch sensitive mat, determining a set of reference corners, performing a comparison of the detected corners of the mat with the set of reference corners, and determining a level of misalignment based on the comparison.

Misalignment detection

An example processor-implemented method for generating corners of a display area is provided. The method comprises detecting a dominant line for each side of the display area, each dominant line used to identify corners, detecting subline segments on each side of the display area, determining a distance between the corners identified by the dominant lines and the sub-line segments on each side, and generating the corners of the display area based on the distance.

Corner generation in a projector display area

Examples disclosed herein relate to aligning content displayed from a projector on to a touch sensitive mat. Examples include detecting a border of the mat, wherein the mat includes a surface area of a first spectral reflectance characteristic on to which the projector is to project the content, and the border of a second spectral reflectance characteristic different from the first spectral reflectance characteristic surrounding a perimeter of the surface area. As an example, detecting the border of the mat generally includes differentiating the second spectral reflectance characteristic of the border from the first spectral reflectance characteristic of the surface area. Examples include detecting a border of the content displayed on to the mat, and adjusting projector settings for the border of the content displayed on to the mat to fit within the detected border of the mat.

Touch sensitive mat of a system with a projector unit

According to one example for segmenting image data, image data comprising color pixel data, IR data, and depth data is received from a sensor. The image data is segmented into a first list of objects based on at least one computed feature of the image data. At least one object type is determined for at least one object in the first list of objects. The segmentation of the first list of objects is refined into a second list of objects based on the at least one object type. In an example, the second list of objects is output.

Image data segmentation

A method and apparatus for aligning a device with a contactor is provided. The apparatus includes a pick and place device, for transporting the device. A first camera acquires an image of the device relative to device holder fiducials of the pick and place device. A second camera detects the location of the contactor relative to fiducials positioned on an alignment frame plate. A third camera to image frame and device holder fiducials to correlate the first and second camera coordinates. Given a processor determines the alignment difference between the device and the contactor. A plurality of actuators align the device with the contactor.

Growing community of inventors

Spring, TX, United States of America

Yun David Tang