A computing device of a first vehicle may receive a first image and a second image of a second vehicle having flashing light signals. The computing device may determine, in the first image and the second image, an image region that bounds the second vehicle such that the image region substantially encompasses the second vehicle. The computing device may determine a polar grid that partitions the image region in the first image and the second image into polar bins, and identify portions of image data exhibiting a change in color and a change in brightness between the first image and the second image. The computing device may determine a type of the flashing light signals and a type of the second vehicle; and accordingly provide instructions to control the first vehicle.

A method and an apparatus for pattern recognition is provided in the present invention, applied to the field of artificial intelligence. The method includes: acquiring a two-dimensional image of a target object and a two-dimensional feature of the target object according to the two-dimensional image of the target object; and acquiring a three-dimensional image of the target object and a three-dimensional feature of the target object according to the three-dimensional image of the target object; identifying the target object according to the two-dimensional feature and the three-dimensional feature of the target object. The method can reduce restrictions on acquiring the image of the target object, for example, reduce the restrictions on the image of the target object in terms of postures, lighting, expressions, make-up and occlusion, thereby improving an accuracy of recognizing the target object and improving a recognition rate and reducing recognition time at the same time.

An image processing device includes: a moving body detecting unit configured to detect a moving body region from a captured image; a setting unit configured to set a reference point and a plurality of straight lines extending radially from the reference point with respect to an image indicating a position and a size of the moving body region in the captured image; a ratio calculating unit configured to calculate a ratio of the moving body region occupying each of the straight lines or each region which is between two adjacent straight lines; and a shadow determining unit configured to determine whether or not a shadow is included in the moving body region based on the number of the straight lines or the regions the ratio of which is equal to or greater than a threshold value.

Apparatus for diagnosing breast cancer, the apparatus comprising a controller having a set of instructions executable to: acquire a contrast enhanced region of interest (CE-ROI) in an X-ray image of a patient's breast, the X-ray image comprising X-ray pixels that indicate intensity of X-rays that passed through the breast to generate the image; determine a texture neighborhood for each of a plurality of X-ray pixels in the CE-ROI, the texture neighborhood for a given X-ray pixel of the plurality of X-ray pixels extending to a bounding pixel radius of BPR pixels from the given pixel; generate a texture feature vector (TF) having components based on the indications of intensity provided by a plurality of X-ray pixels in the CE-ROI that are located within the texture neighborhood; and use a classifier to classify the texture feature vector TF to determine whether the CE-ROI is malignant.

A computer-implemented detection method includes, in response to inputting a first image including a region of one or more objects to a learned model, identifying a first entire image corresponding to entirety of a first object as a detection candidate, the learned model being generated by learning training data including an image corresponding to a part of an object and an entire image corresponding to entirety of the object, detecting an existing region of the first target object in the first image in accordance with a comparison between the identified first entire image and the region of the one or more target objects, and determining, based on a specific image obtained by invalidating the existing region in the first image, whether another target object is included in the first image.

A head mounted display (HMD) comprises an eye tracking system configured to perform a calibration process using an eye tracking system of the HMD that includes determining a pupillary axis and/or determining an angular offset between the pupillary axis and the eye's true line of sight. The eye tracking system obtains an eye model captures images of the user's pupil while the user is looking at a target or other content displayed on the HMD. In some embodiments, the calibration process is based on a single image of the user's eye and is performed only once. For example, the process can be performed the first time the user uses the HMD, which stores the calibration data for the user in a memory for future use.

A vacant parking space detection apparatus according to the present disclosure includes a memory and a hardware processor coupled to the memory. The hardware processor is configured to: generate, for each of divided regions in a region around a vehicle, map information representing a presence probability of an object based on a detection result of a sensor for detecting an object present around the vehicle; define on the map information a plurality of first straight lines, whose intercepts differ from each other, with one or more angles to a straight advancing direction of the vehicle; and detect whether a vacant parking space is present at the angle based on a presence probability of an object assigned to the divided region belonging to each of the plurality of first straight lines.

An image processing apparatus includes a first memory used for first rearrangement processing on a group of pixels in an input image, and a second memory used for second rearrangement processing on a group of pixels in an image obtained by the first rearrangement processing, and performs correction processing that includes the first rearrangement processing and the second rearrangement processing on the input image. One of the first and second memories is capable of higher-speed random access than the other memory and has a smaller memory capacity than the other memory. One of the first rearrangement processing and the second rearrangement processing is processing for rearranging a group of pixels in each of a plurality of block images generated from the input image, and the other rearrangement processing is processing for rearranging pixel rows among the block images. The one rearrangement processing involves random access to the one memory.

This invention provides an information processing apparatus which comprises an image acquiring unit configured to acquire images captured by a plurality of image capturing devices, a contour extracting unit configured to extract a contour of an object from the image acquired by the image capturing device, a matching unit configured to match corresponding points on the contours between the images, a depth calculating unit configured to calculate a depth of the matched point, a reliability extracting unit configured to acquire a reliability of the depth based on an angle formed by an epipolar line and a tangential direction of the contour, and a depth correcting unit configured to correct the depth based on the depth and the reliability.

Provided is a segment-block-based handwritten signature authentication system and a method thereof, and more particularly, to a handwritten signature authentication system and a method thereof that enrolls a handwritten signature including handwritten signature characteristics information based on segment blocks disjointed by a user, acquires segment-block-based handwritten signature characteristics information from the handwritten signature upon request for handwritten signature authentication, and performs handwritten signature authentication by comparing the pre-enrolled handwritten signature characteristics information based on segments and the acquired handwritten signature characteristics information.