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.

A shape discriminating device includes an image acquisition means configured to acquire a target image being an image where pants are shown, a diverging position acquisition means configured to acquire, as a diverging position, a position where the pants diverge into two leg parts or a position which can be regarded as a position where the pants diverge into two leg parts, a leg region extraction means configured to extract a leg region from a region showing the pants in the target image, a leg shape acquisition means configured to acquire leg shape information concerning variation in lateral width of a leg part of the pants based on the diverging position and the leg region, a specifying means configured to specify a shape of the pants based on the leg shape information, and an output means configured to output information concerning the specified shape of the pants.

In an embodiment, a pose estimation device obtains an image of an object, and generates a pose estimate of the object. The pose estimate includes a respective heatmap for each of a plurality of pose components of a pose of the object, and the respective heatmap for each of the pose components includes a respective uncertainty indication of an uncertainty of the pose component at each of one or more pixels of the image.

The present disclosure includes systems, methods, and non-transitory computer readable media that efficiently and accurately identify matching designs and sub-shapes across one or more digital canvases in order to provide one or more development tools for rapid and efficient editing of the digital canvases. In particular, one or more embodiments utilize a transformation-agnostic method of identifying matching designs and sub-shapes between multiple digital canvases. Furthermore, in response to identifying a set of matching designs or sub-shapes, one or more embodiments generate a mapping between the matching designs or sub-shapes. Utilizing this mapping, one or more embodiments provide various tools that enable rapid and efficient development of robust digital canvases, while minimizing system storage burdens.

Apparatus for an automatic identification of medically relevant video elements, the apparatus comprising a data input, configured to receive a data stream of image slices, wherein the data stream of image slices represents a temporal course of a view of image slices defined by a masking strip of video images from a video which has been recorded during a medical surgery on a patient an analysis apparatus configured to analyze the data stream of image slices via an analysis comprising at least one predefined analysis step for the presence of at least one sought-for feature and to output a result of the presence, and a processing device configured to output a start mark which indicates a correspondence between the presence and a position in the data stream of image slices if the result indicates the presence of the sought-for feature. Also, a corresponding method is disclosed.

A gesture recognition method and a gesture recognition device are provided. The gesture recognition method includes the steps of: obtaining a hand image including a gesture graphic; determining a reference point in the gesture graphic; determining circular arc reference lines by using the reference point as a center; determining intersection points of each of the circular arc reference lines intersecting with a boundary of the gesture graphic; determining whether at least two finger blocks of a plurality of finger blocks of the gesture graphic conform to an approaching trend according to the circular arc reference lines and the intersection points, and determining whether the at least two finger blocks in a selected range of the gesture graphic forms a continuous graphic block; and when the at least two finger blocks of the gesture graphic conform to the approaching trend and form the continuous graphic block, determining the hand image as a hand pinch image.

Embodiments of the present disclosure provide a method and apparatus for detecting a license plate. The method comprises: obtaining, according to pixel values of pixels in an image to be detected, a candidate license plate area M.sub.1 in the image to be detected (S101); calculating an aspect ratio of the candidate license plate area M.sub.1 and determining if the aspect ratio is greater than a first predefined threshold (S102); determining, if the aspect ratio is greater than the first predefined threshold, a new candidate license plate area M.sub.2 from the candidate license plate area M.sub.1 according to a predefined machine learning-based regression algorithm (S103); determining, according to a first predefined classification model, whether the candidate license plate area M.sub.2 is a license plate area (S104); determining, if the candidate license plate area M.sub.2 is a license plate area, the candidate license plate area M.sub.2 as a license plate area, and generating a detection result based on the candidate license plate area M.sub.2 (S105). The application of the solution improves the accuracy of license plate detection.

An apparatus includes a display control unit, a receiving unit, an adjusting unit, and a determination unit. The display control unit is configured to display an image showing a result of detection of a defect from a captured image of a structure on a display device. The receiving unit is configured to receive an operation to specify part of the displayed image as a first region and an operation to give an instruction to correct at least part of the detection data corresponding to the first region. The adjusting unit is configured to adjust a parameter to be applied to the first region according to the instruction. The determination unit is configured to determine one or more second regions to which the adjusted parameter is to be applied from a plurality of segmented regions of the image.

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.

Apparatus for an automatic identification of medically relevant video elements, the apparatus including a data input, configured to receive a data stream of image slices, wherein the data stream of image slices represents a temporal course of a view of image slices defined by a masking strip of video images from a video which has been recorded during a medical surgery on a patient an analysis apparatus configured to analyze the data stream of image slices via an analysis including at least one predefined analysis step for the presence of at least one sought-for feature and to output a result of the presence, and a processing device configured to output a start mark which indicates a correspondence between the presence and a position in the data stream of image slices if the result indicates the presence of the sought-for feature. Also, a corresponding method is disclosed.