A method, system, apparatus, article of manufacture, and computer-readable storage medium provide the ability to merge multiple point cloud scans. A first raw scan file and a second raw scan file (each including multiple points) are imported. The scan files are segmented by extracting segments based on geometry in the scene. The segments are filtered to reduce a number of segments and identify features. A set of candidate matching feature pairs are acquired by coarsely registering features from one scan to features from another scan. The candidate pairs are refined by improving alignment based on corresponding points in the features. The candidate pairs are scored and then merged based on the scores.

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.

Free space machine interface and control can be facilitated by predictive entities useful in interpreting a control object's position and/or motion (including objects having one or more articulating members, i.e., humans and/or animals and/or machines). Predictive entities can be driven using motion information captured using image information or the equivalents. Predictive information can be improved applying techniques for correlating with information from observations.

A conversion model construction device updates a generation module to process a first training image of a first type into a conversion image by using a separation outline module, updates the generation module to process the conversion image into a shape of a second training image of a second type by using a shape inference module, and trains the conversion model by updating the generation module such that the conversion image is determined as a real image by a discriminator module. The separation outline module separates a polygon of an input image from a background and distinguishes an outline, the shape inference module compares a border shape of a polygon included in the first image with a border shape of a polygon included in the second image and the discriminator module determines whether the input image is a real image or a fake image according to the set condition.

A medical imaging device includes: a display configured to display first and second medical images having different modalities from each other with respect to an object: an image processor configured to match the first and second medical images, extract a second object corresponding to a first object selected in the first medical image from the second medical image, extract first feature information of the first object by analyzing the first medical image, and extract second feature information of the second object by analyzing the second medical image: and a controller configured to generate final diagnostic information based on the first and second feature information, and control the display to display the final diagnostic information.

A method for an electronic device to control an object includes recognizing a first object and a second object, identifying a first attribute of the first object and a second attribute of the second object, selecting an object to control based on the first attribute and the second attribute, generating an operation signal for the selected object, and transmitting the generated operation signal to the selected object.

An object detection device of an object detection system includes an object detection determination unit including a bird candidate determination unit for determining, from an image acquired by imaging a moving object, whether or not the moving object is a specific detection subject (bird in this case), and a bird type/attitude estimation unit for estimating, based on a contour of the moving object determined to be the bird by the bird candidate determination unit and a WFM library storing contour shape information, which is a contour prepared for each of types of the specific detection subject (types of the bird in this case), a type of the moving object out of the types of the specific detection subject.

In an example embodiment a method, apparatus and computer program product are provided. The method includes calculating directionality values for pixels of a first image and pixels of a second image, where a directionality value for a pixel is calculated based on gradient differences between the pixel and a plurality of neighboring pixels. The method includes determining a plurality of similarity values between the first image and the second images for a plurality of alignment positions of the first image and the second image based on the directionality values for the pixels of the first image and the directionality values for corresponding pixels of the second image. The method further includes selecting an alignment position from among the plurality of alignment positions for aligning the first image and the second image based on comparison of the plurality of similarity values.

Described herein is a computer implemented method. The method includes retrieving original drawing data that includes an ordered set of original drawing points that define an input shape, the original drawing data being associated with a first template shape type. The method further includes generating a plurality of synthetic shapes. Each synthetic shape is defined by an ordered set of synthetic shape points, and generating a particular synthetic shape includes performing a first operation that is based on the original drawing data. For each synthetic shape a training example is generated that includes the synthetic shape and is associated with the first template shape type.

Free space machine interface and control can be facilitated by predictive entities useful in interpreting a control object's position and/or motion (including objects having one or more articulating members, i.e., humans and/or animals and/or machines). Predictive entities can be driven using motion information captured using image information or the equivalents. Predictive information can be improved applying techniques for correlating with information from observations.