A method for denoising a range image acquired by a time-of-flight (ToF) camera by first determining locations of edges, and a confidence value of each pixel, and based on the locations of the edges, determining geodesic distances of neighboring pixels. Based on the confidence values, reliabilities of the neighboring pixels are determined and scene dependent noise is reduced using a filter.

Precise analysis and description of movement and gestures by a human or other object are carried out by a computing device assisted by camera and distance sensors. The same gestures and movements of an object in different locations and in different orientations may be identified according to coordinates and offsets applied to coordinates, and gesture-making areas projected so as to surround the object. The techniques can accurately identify actions of movements of the human or other object.

A system for the conversion of video from one frame rate to a different frame rate. The system includes the application of graphical element and text detection and processing in frame rate up conversion.

Techniques related to eye contact correction to provide a virtual user gaze aligned with a camera while the user views a display are discussed. Such techniques may include encoding an eye region of a source image using a pretrained neural network to generate compressed features, applying a pretrained classifier to the features to determine a motion vector field for the eye region, and warping and inserting the eye region into the source image to generate an eye contact corrected image.

A method includes: extracting a first line segment pair including a combination of line segments selected from a plurality of line segments included in an image of a form to be recognized; calculating a first feature amount which represents a relationship between the line segments in the extracted first line segment pair; extracting a candidate for a form identifier of the form to be recognized based at least on the calculated first feature amount and a second feature amount in line segments in a second line segment pair correlated with a form identifier which is registered in advance; extracting corresponding line segment pairs which include a line segment correlated with the candidate for the form identifier and a line segment of the form to be recognized; and specifying the form identifier of the form to be recognized based at least on the degree of overlapping.

The present disclosure relates to systems and processes for providing vector map data for generating a view of a map in a mapping application. In one example process, a request for a vector map sub-tile can be received by a map server. The map server can identify a pre-generated vector map tile corresponding to the requested vector map sub-tile and can generate the requested vector map sub-tile from the identified vector map tile by dividing the vector map tile into two or more vector map sub-tiles. In some examples, dividing the vector map tile into multiple vector map sub-tiles can include identifying features and attributes of the vector map tile that should be included in the requested vector map sub-tile and generating the requested vector map sub-tile to include these features and attributes. The map server can then transmit the requested vector map sub-tile to the requesting electronic device.

A control method for a robot cleaner includes acquiring a plurality of images of surroundings during travel of the robot cleaner in a cleaning area, estimating a plurality of room-specific feature distributions according to a rule defined for each of a plurality of rooms, based on the images acquired while acquiring the plurality of images, acquiring an image of surroundings at a current position of the robot cleaner, obtaining a comparison reference group including a plurality of room feature distributions by applying the rule for each of the plurality of rooms to the image acquired while acquiring the image at the current position, comparing the obtained comparison reference group with the estimated room-specific feature distributions, and determining a room from the plurality of rooms having the robot cleaner currently located therein.

An imaging system includes an image sensor to capture a sequence of images, including a low dynamic range (LDR) image and a high dynamic range (HDR) image, and a processor coupled to the image sensor to receive the LDR image and the HDR image. The processor receives instructions to perform operations to segment the LDR image and HDR image into a plurality of segments. The processor also scans the plurality of LDR and HDR image segments to find a first image segment in the plurality of LDR image segments and a second image segment in the plurality of HDR image segments. The processor then finds interest points in the first and second image segments, and determines an alignment parameter based on matched interest points. The LDR image and the HDR image are combined in accordance with the alignment parameter.

A first arithmetic apparatus performs an arithmetic process, out of a plurality of arithmetic processes in identification processing on an input image, in which the parameter amount that is used is small compared to an amount of data to which the parameters are applied. A second arithmetic apparatus performs an arithmetic process, out of the plurality of arithmetic processes, in which the parameter amount that is used is large compared to an amount of data to which the parameters are applied. The second arithmetic apparatus can use a larger memory capacity memory than the first arithmetic apparatus.

A medical image processing apparatus includes a port, a processor and a display. The port acquires volume data including a subject. The processor generates an image based on the volume data. The display shows the generated image. A pixel value of at least one pixel of the image is defined based on (i) a statistical value of voxel values of voxels in a predetermined range on a virtual ray projected to the volume data and (ii) shading of a contour of the subject at a predetermined position on the virtual ray.