A method comprises capturing, with a vehicle vision sensor, a color image of a landing site including landing surface markers; converting the color image to a gray scale image; and performing multi-scale-binarization to detect multiple edges of the gray scale image and produce binary images. The method determines contours of edges of the binary images having closed shapes, detects closed shapes of contours of edges having four corners, and verifies whether four-sided candidate contours are valid as potential landing surface markers. If more than one contour is associated with a valid ID within a surface marker library, then the contour within the smallest window size is selected. If multiple contours with the same window size can be associated with a valid ID, then a mean of corresponding corners of multiple contours is computed. The method then performs corner refinement of valid four-sided candidate contours identified as potential landing surface markers.

A system and method that transforms data formats into contour metrics and further transforms each contour of that mapping into contours pattern metric sets so that each metric created has a representation of one level of contour presentation, at each iteration of the learning contour identification system defined herein. This transformation of data instance to contour metrics permits a user to take relevant data of a data set, as determined by a learning contour identification system, to machines of other types and function, for the purpose of further analysis of the patterns found and labeled by said system. The invention performs with data format representations, not limited to, signals, images, or waveform embodiments so as to identify, track, or detect patterns of, amplitudes, frequencies, phases, and density functions, within the data case and then by way of using combinations of statistical, feedback adaptive, classification, training algorithm metrics stored in hardware, identifies patterns in past data cases that repeat in future, or present data cases, so that high-percentage labeling and identification is a achieved.

The utility model relates to a HMI system based on a 3D TOTO word card, comprising a verification activation module, a scanning module, a identification module, a matching module, a display module, a camera module, a help module, a interaction module, a storage module, a sharing module and a CPU. The scanning module comprises a single-card scanning module, a combined scanning module and an experience scanning module. The verification activation module, scanning module, identification module, matching module, display module, camera module, help module, interaction module, storage module and share module are connected with CPU, respectively. The utility model increases children's practical ability in the cognitive process of Chinese characters and improves Children's participation in the cognitive process of Chinese characters, thus improving Childeren's efficiency and fun of cognition of Chinese characters; in addition, when entering the system, the customers need to get a verification code from the merchant, and activate the system by verification activation module, to facilitate the merchant to provide customers with other follow-up services, such as notification sending or password extracting.

A system can locate patterns for measurement in a captured Scanning Electron Microscope (SEM) image. The system can include a processor circuit that can be configured to generate a target pattern from a layout of a semiconductor device, and configured to generate a virtual image that corresponds to the target pattern, wherein elements of the virtual image less than completely overlap the corresponding portions of the target pattern, and configured to locate portions of a captured SEM image of a fabricated semiconductor device that match the elements of the virtual image.

A shape similarity metric can be provided that indicates how similar two or more shapes are. A difference between a union of the shapes and an intersection of the shapes can be used to determine the similarity metric. The shape similarity metric can provide an average distance between the shapes. Different processes for determining shapes can be evaluated for accuracy based on the shape similarity metric. New or alternative shape-determining processes can be compared for accuracy against other shape-determining processes including reference shape-determining processes. Shape similarity metrics can be determined for two-dimensional shapes and three-dimensional shapes.

A headphone for spatial audio rendering includes a first database having an impulse response pair corresponding to a reference speaker location. A head sensor provides head orientation information to a second database having rotation filters, the filters corresponding to different azimuth and elevation positions relative to the reference speaker location. A digital signal processor combines the rotation filters with the impulse response pair to generate an output binaural audio signal to transducers of the headphone. Efficiencies in creating impulse response or HRTF databases are achieved by sampling the impulse response less frequently than in conventional methods. This sampling at coarser intervals reduces the number of data measurements required to generate a spherical grid and reduces the time involved in capturing the impulse responses. Impulse responses for data points falling between the sampled data points are generated by interpolating in the frequency domain.

An architecture for linear-time extraction of maximally stable extremal regions (MSERs) having an image memory, heap memory, a pointer array and processing hardware is disclosed. The processing hardware is configured to in real-time analyze image pixels in the image memory using a linear-time algorithm to identify a plurality of components of the image. The processing hardware is also configured to place the image pixels in the heap memory for each of the plurality of components of the image, generate a pointer that points to a location in the heap memory that is associated with a start of flooding for another component and store the pointer in the array of pointers. The processing hardware is also configured to access the plurality of components using the array of pointers and determine MSER ellipses based on the components and MSER criteria.

When a hand of the user is recognized in an image pickup region of a camera, a head mounted display stores a contour shape of the hand which would be imaged by the camera in advance. In addition, the head mounted display receives an input of image data per pixel included in the camera, calculates a difference between colors of adjacent pixels represented by the image data, sets a set of image data having the same color system, where the calculated difference is within a predetermined threshold, as a group, and captures a contour of a region of the data. Next, the head mounted display compares the captured contour to a contour shape of the hand which is stored in advance to allow the user to recognize the hand of the user in the image pickup region.

Provided is a new method which creates the virtual garment from a single photograph of a real garment put on to the mannequin. The method uses the pattern drafting theory in the clothing field. The drafting process is abstracted into a computer module, which takes the garment type and primary body sizes then produces the draft as the output. Then the problem is reduced to find out the garment type and primary body sizes. That information is found by analyzing the silhouette of the garment with respect to the mannequin. The method works robustly and produces practically usable virtual clothes that can be used for the graphical coordination.

Disclosed herein are embodiments of an image-recognition based game. In one aspect, a method involves (1) receiving by a computing device an input to initiate a game application, (2) causing the game application to initiate a game, and (3) during gameplay of the game: (a) causing a graphical display of the computing device to display a silhouette object that includes at least a shape of the silhouette object, (b) receiving by the computing device image data of an environment that includes a real-world object, (c) analyzing the image data to determine one or more similarity measures that indicate similarity between the real-world object and the silhouette object, where one of the similarity measures indicates similarity between a shape of the real-world object and the shape of the silhouette object, and (d) causing the graphical display to display a match indication based on the one or more similarity measures.