A system and a method of sorting scrap particles includes imaging a moving conveyor containing scrap particles using a vision system to create an image. A computer analyzes the image as a matrix of cells, identifies cells in the matrix containing a particle, and calculates a color input for the particle from a color model by determining color components for each cell associated with the particle. A light beam is directed to the particle on the conveyor downstream of the vision system, and at least one emitted band of light from the particle is isolated and detected at a selected frequency band to provide spectral data for the particle. The computer generates a vector for the particle containing the color input and the spectral data, and classifies the particle into one of at least two classifications of a material as a function of the vector.

Embodiments of the present invention disclose an object detection method and a computer device. The method includes: obtaining a to-be-processed image; obtaining, according to the to-be-processed image, n reference regions used to identify a to-be-detected object in the to-be-processed image, and n detection accuracy values, of the to-be-detected object, corresponding to the n reference regions; determining sample reference regions in the n reference regions, where coincidence degrees of the sample reference regions is greater than a preset threshold; and determining, based on the sample reference regions, a target region corresponding to the to-be-detected object, where the target region is used to identify the to-be-detected object in the to-be-processed image. Implementation of the embodiments of the present invention helps improve accuracy of detecting a location of an object.

A normalization method in grouped feature data for recognizing human cognitive states, comprising: (1) divide feature data into groups; (2) selecting normalization functions and estimating grouping parameters; (3) building grouped normalization functions, substitute normalization function parameters of each group into its normalization function, the normalization mapping relationship of each group is get; (4) grouped normalization processing, each group uses corresponding normalization function to transfer the feature data to finish feature normalization. The entire feature normalization method can only solve the divers data distribution problem between feature and feature, it can not solve the problem of the large difference of inner data distribution, the grouped normalization methods provided in the invention reserve the advantages of entire feature normalization method, while at the same time, the large inner distribution of feature data is reduced, the accuracy of classification is improved, the grouped normalization method in the invention have strong robustness.

An object detection apparatus is capable of estimating the size of a moving object easily based on images. An object detection apparatus (5) of an object detection system (1) includes an object detection/determination unit (7) configured to analyze a period of motion of the object based on the images to estimate a size of the object based on the period of motion of the object.

The invention provides methods of detecting and describing features from an intensity image. In one of several aspects, the method comprises the steps of providing an intensity image captured by a capturing device, providing a method for determining a depth of at least one element in the intensity image, in a feature detection process detecting at least one feature in the intensity image, wherein the feature detection is performed by processing image intensity information of the intensity image at a scale which depends on the depth of at least one element in the intensity image, and providing a feature descriptor of the at least one detected feature. For example, the feature descriptor contains at least one first parameter based on information provided by the intensity image and at least one second parameter which is indicative of the scale.

Identifying a local coordinate system is described for gesture recognition. In one example, a method includes receiving a gesture from a user across a horizontal axis at a depth camera, determining a horizontal vector for the user based on the received user gesture, determining a vertical vector; and determining a rotation matrix to convert positions of user gestures received by the camera to a frame of reference of the user.

Disclosed are embodiments of in-situ display monitoring and calibration systems and methods. An image acquisition system captures images of the viewing plane of the display. Captured images may then be processed to characterize various visual performance characteristics of the display. When not in use capturing images of the display, the image acquisition system can be stored in a manner that protects it from environmental hazards such as dust, dirt, precipitation, direct sunlight, etc. A calibration image in which a plurality of light emitting elements is set to a particular color and intensity may be displayed, an image then captured, and then a difference between what was expected and what was captured may be developed for each light emitting element. Differences between captured images and expected images may be used to create a calibration data set which then may be used to adjust the display of further images upon the display.

A lane departure warning method includes steps of: collecting a road image by an imaging device; detecting a lane marking in accordance with the road image, so as to extract a position of the lane marking and an angle of the lane marking relative to a running direction of the vehicle; acquiring steering information and a movement speed of the vehicle by an OBD system; judging whether or not the vehicle is unconsciously running on the lane marking in accordance with the position of the lane marking, the angle of the lane marking relative to the running direction of the vehicle and the steering information of the vehicle; in the case that the vehicle is unconsciously running on the lane marking, recording a duration within which the vehicle is unconsciously running on the lane marking; and judging whether or not to send a lane departure warning to the vehicle.

The present invention addresses the problem of acquiring information regarding a component or product and identifying said component or product easily and inexpensively. The present invention has an image-feature storage, an extracting means, an acquiring means, and an identifying means. The image-feature storage stores image features of texture patterns formed on components or products. The extracting means extracts an n-dimensional-symbol image and a texture-pattern image from a taken image containing at least the following: an n-dimensional symbol (n being a natural number) that represents information regarding a component, a product, or a product comprising said component; and a texture pattern formed on said component or product. The acquiring means acquires, from the extracted n-dimensional-symbol image, the aforementioned information regarding the component or product. The identifying means identifies the component, product, or component-comprising product by matching image features of the extracted texture-pattern image against the image features stored by the image-feature storage.

A method for comparing videos of a surgical procedure is disclosed. The method comprising selecting a plurality of videos from a surgical video database. Each of the plurality of videos including video data of a first surgical procedure comprising a plurality of surgical steps. The method further including identifying a first surgical step included in the plurality of surgical steps within a first video segment in each of the plurality of videos. The method also including warping the first video segment to standardize a dimension of the first video segment in each of the plurality of videos.