A control device includes a storage device which has stored a program, and a hardware processor, in which the hardware processor executes the program stored in the storage device, thereby acquiring a peripheral image of the mobile object, which is an image captured by a fisheye camera mounted on a mobile object, calculating an instruction regarding future traveling of the mobile object as a base trajectory in an orthogonal coordinate system, coordinate-converting the acquired base trajectory in the orthogonal coordinate system into a base trajectory in a fisheye camera coordinate system, calculating a risk of the base trajectory in the fisheye camera coordinate system on the basis of the peripheral image, and the base trajectory in the fisheye camera coordinate system, and calculating a traveling trajectory by modifying the base trajectory in the orthogonal coordinate system on the basis of the risk of the base trajectory in the fisheye camera coordinate system.

Disclosed is a distortion rectification method, comprising: taking a wide-angle photograph using a camera of a terminal; determining distortion regions and non-distortion regions in the wide-angle photograph; obtaining a target distortion region selected by a user; dividing the target distortion region into M grid regions of a first pre-set size, wherein M is an integer greater than or equal to one; and respectively performing distortion rectification on the M grid regions of the first pre-set size. Also disclosed is a terminal.

One disclosed example provides a videoconferencing system comprising a processor and a storage device storing instructions executable by the processor to obtain an image of a scene acquired via a camera, the image of the scene comprising image distortion arising from a camera pitch angle at which the image of the scene was acquired. The instructions are further executable to apply a projection mapping to the image of the scene to map the image of the scene to a projection comprising a tilt parameter that is based upon the camera pitch angle at which the image of the scene was acquired, thereby obtaining a corrected image, and output the corrected image.

When a first user makes a video call with a second user of the other side by using the video call function, a first state is set as a state in which the enclosure is flatly placed on a first surface of an object, and in which a face of the first user is included within a range of an angle of view AV1 of the front camera C1. In the first state, the mobile information terminal 1 detects a first region including the face of the first user from a wide angle image that is captured by the front camera C1, trims a first image corresponding to the first region, creates a transmission image to be transmitted to a terminal of the other side on the basis of the first image, and transmits the transmission image to the terminal of the other side.

A system for creating synthetic data for testing an autonomous system, comprising at least one hardware processor adapted to execute a code for: using a machine learning model to compute a plurality of depth maps based on a plurality of real signals captured simultaneously from a common physical scene, each of the plurality of real signals are captured by one of a plurality of sensors, each of the plurality of computed depth maps qualifies one of the plurality of real signals; applying a point of view transformation to the plurality of real signals and the plurality of depth maps, to produce synthetic data simulating a possible signal captured from the common physical scene by a target sensor in an identified position relative to the plurality of sensors; and providing the synthetic data to at least one testing engine to test an autonomous system comprising the target sensor.

An image controller, an image processing system, and an image correcting method are provided. A first controller obtains a first image from an image capturing apparatus. The first controller converts the first image into a second image according to a converting operation. The converting operation includes deformation correction, and the deformation correction is used to correct deformation of one or more target objects in the first image. A second controller detects the target object in the second image to generate a detected result. The first controller corrects the converting operation according to the detected result. A visual experience may thus be improved in this way.

An image processing method for receiving M lens images and generating a projection image is disclosed. The method comprises: determining P optimal warping coefficients of P control regions in the projection image according to a 2D error table and the M lens images from an image capture module; generating M projection images according to the M lens images, a first vertex list and the P optimal warping coefficients; determining a seam for each of N seam regions; and, stitching two overlapping seam images to generate a stitched seam image for each seam region according to its corresponding seam. The 2D error table comprises multiple test warping coefficients and multiple accumulation pixel value differences in the P control regions. The P control regions are respectively located in the N seam regions respectively located in N overlap regions, where M>=2, N>=1 and P>=3.

A method for dewarping a region of a fisheye view image , captured by a fisheye lens wherein the fisheye view image comprises a first dewarping pole, DP1. The method defines a region of interest, ROI, determining a center, G, of the ROI, defining a temporary annulus sector region such that the temporary annulus sector region comprises the ROI, and has its center at DP1 and has a temporary outer arc shaped edge and a temporary inner arc shaped edge, defining a second dewarping pole, DP2 at a distance, D, from DP1 along a radial direction extending from G of the ROI through the DP1, setting a dewarping annulus sector region comprising the ROI. The dewarping annulus sector region has its center at DP2 and has its dewarping inner arc shaped edge maintained at a same radial distance from DP1 as the temporary inner arc shaped edge.

There is provided an image processing apparatus comprising: a processor; and a memory storing a program. When the program is executed by the processor, the program causes the image processing apparatus to: obtain a first RAW image including a region of a first circular fisheye image; and develop the first RAW image. A pixel outside the region of the first circular fisheye image in the first RAW image is not developed.

A computer, including a processor and a memory, the memory including instructions to be executed by the processor to input a fisheye image to a vector quantized variational autoencoder. The vector quantized variational autoencoder can encode the fisheye image to first latent variables based on an encoder. The vector quantized variational autoencoder can quantize the first latent variables to generate second latent variables based on a dictionary of embeddings. The vector quantized variational autoencoder can decode the second latent variables to a rectified rectilinear image using a decoder and output the rectified rectilinear image.