G06V10/75

ENHANCED ANIMATION GENERATION BASED ON MOTION MATCHING USING LOCAL BONE PHASES

Systems and methods are provided for enhanced animation generation based on using motion mapping with local bone phases. An example method includes accessing first animation control information generated for a first frame of an electronic game including local bone phases representing phase information associated with contacts of a plurality of rigid bodies of an in-game character with an in-game environment. Executing a local motion matching process for each of the plurality of local bone phases and generating a second pose of the character model based on the plurality of matched local poses for a second frame of the electronic game.

IMAGE PROCESSING DEVICE OF PERSON DETECTION SYSTEM

An image processing device of a person detection system mounted on a moving body is configured to: detect, in image data obtained from a camera, an area in which an obstacle appears; determine whether the area meets an upper body detection process condition that the obstacle in the area is distanced from a road surface within a predetermined range from the camera; perform an upper body detection process in which the area of the image data is compared with upper body comparison data to determine whether the obstacle in the area is a person, for the area that meets the upper body detection process condition; and perform a whole-body detection process in which the area of the image data is compared with whole-body comparison data to determine whether the obstacle in the area is a person, for the area that does not meet the upper body detection process condition.

SAMPLE OBSERVATION SYSTEM AND IMAGE PROCESSING METHOD
20230005123 · 2023-01-05 ·

The invention provides a sample observation system including a scanning electron microscope and a calculator. The calculator: (1) acquires a plurality of images captured by the scanning electron microscope; (2) acquires, from the plurality of images, a learning defect image including a defect portion and a learning reference image not including the defect portion; (3) calculates estimation processing parameters by using the learning defect image and the learning reference image; (4) acquires an inspection defect image including a defect portion; and (5) estimates a pseudo reference image by using the estimation processing parameters and the inspection defect image.

METHOD AND SYSTEM FOR CROP LOSS ESTIMATION

Crop loss estimation allows a user to monitor and estimate damage to the crops due to various natural events/factors. State of the art systems used for the crop loss estimation have the disadvantage that they do not convey to the users extent of damage. In addition to this, the existing methods do not take into account the recovery factor of the crops due to multiple factors and end up in overestimating the loss. The disclosure herein generally relates to crop monitoring, and, more particularly, to a method and system for crop loss estimation. In this method, crop loss is assessed based on real-time weather parameters and remote sensing data collected and processed, and crops are classified as being in one of a repairable damage class and a permanent damage class. The system also quantifies the crop loss, which allows the user to understand magnitude of the crop loss.

ANALYSIS DEVICE AND COMPUTER-READABLE RECORDING MEDIUM STORING ANALYSIS PROGRAM

An analysis device includes a processor configured to: execute a first learning process on a generative model for images such that the images that bring a recognition result of an image recognition process into a preassigned state are generated; execute a second learning process on the generative model on which the first learning process has been executed, while gradually changing recognition accuracy of the images generated by the generative model on which the first learning process has been executed, to desired recognition accuracy; acquire each piece of information on back-error propagation calculated by executing the image recognition process, for the images with each level of the recognition accuracy generated through a course of the second learning process; and generate evaluation information indicating each of image parts that cause erroneous recognition at each level of the recognition accuracy, based on the acquired each piece of the information on the back-error propagation.

Adaptive video streaming

A method, system and apparatus for image capture, analysis and transmission are provided. A link aggregation method involves identifying controller network ports to a source connected to the same subnetwork; producing packets associating corresponding controller network ports selected by the source CPU for substantially uniform selection; and transmitting the packets to their corresponding network ports. An image analysis method involves producing by a camera an indication whether a region of an image differs by a threshold extent from a corresponding region of a reference image; transmitting the indication and image data to a controller via a communications network; and storing at the controller the image data and the indication in association therewith. The controller may perform operations according to positive indications. A transmission method involves receiving user input in respect of a video stream and transmitting, in accordance with the user input, selected data packets of selected image frames thereof.

Registration of a surgical image acquisition device using contour signatures

Registration of a surgical image acquisition device (e.g. an endoscope) using preoperative and live contour signatures of an anatomical object is described. A control unit includes a processor configured to compare the real-time contour signature to the database of preoperative contour signatures of the anatomical object to generate a group of potential contour signature matches for selection of a final contour match. Registration of an image acquisition device to the surgical site is realized based upon an orientation corresponding to the selected final contour signature match.

Control system, control method, and non-transitory storage medium
11567509 · 2023-01-31 · ·

According the present invention, there is provided a control system (10) that includes an image acquisition unit (11) that acquires an image generated by a camera, a controlled object determination unit (12) that analyzes the image and determines at least one of a vehicle that satisfies a predetermined condition and a vehicle in which a predetermined person is riding included in the image, as a vehicle to be controlled, a control content decision unit (13) that decides a control content for the vehicle to be controlled, and an output unit (14) that outputs a control command including the control content to the vehicle to be controlled.

Systems and methods for generating summaries of missed portions of media assets

A media guidance application may determine a length of a portion of a media asset that the user has missed and compare the length with a threshold length. If the length is greater than the threshold length, the media guidance application may generate a first summary of the missed portion of the media asset based on segments of the missed portion of the media asset that are of a first importance. If the length is not greater than the threshold length, the media guidance application may generate a second summary of the missed portion of the media asset based on segments of the missed portion of the media asset that are of the first importance and the second importance. The media guidance application may generate for display the summary.

Systems and methods for matching color and appearance of target coatings

System and methods for matching color and appearance of a target coating are provided herein. The system includes an electronic imaging device configured to receive a target image data of the target coating. The target image data includes target coating features. The system further includes one or more feature extraction algorithms that extracts the target image features from the target image data. The system further includes a machine-learning model that identifies a calculated match sample image from a plurality of sample images utilizing the target image features. The machine-learning model includes pre-specified matching criteria representing the plurality of sample images for identifying the calculated match sample image from the plurality of sample images. The calculated match sample image is utilized for matching color and appearance of the target coating.