According to this feature point recognition system (1), data of a feature point of a first group obtained by a first algorithm calculation unit (12) with no mask processing is compared with data of a feature point of a second group detected by a third algorithm calculation unit (16) obtained through mask processing performed by a second algorithm calculation unit (14), whether the data is abnormal is determined, and thereby feature points of a subject P can be recognized more accurately and stably than in the related art.

A method, apparatus, and system with tracking are disclosed. The apparatus is configured to acquire a feature map of a template image, a color histogram of a foreground of the template image that has an object, and a color histogram of a background of the template image other than the foreground, acquire a feature score map, and a bounding box map corresponding to the feature score map, based on the feature map of the template image and a feature map of a search image, acquire a color score map based on the color histogram of the foreground, the color histogram of the background, and a color value of the search image, acquire a final score map, and a bounding box map corresponding to the final score map, based on the feature score map, the color score map, and the bounding box map, and output the corresponding bounding box.

A device for recognizing an obstacle of a vehicle includes a camera for acquiring an image, a detection device for extracting an object by applying a convolutional neural network to the image, a center calculation device for estimating a center point and a region outside the center point of the extracted object, an uncertainty determination device for determining whether the estimated center point and region outside the center point are uncertain, and a condition determination device for determining whether travel is possible based on the determined uncertainty.

A measuring device including: a stereo image acquiring unit configured to acquire a first image of a first viewpoint and a second image of a second viewpoint at a predetermined first time and acquire a third image of the first viewpoint and a fourth image of the second viewpoint at a second time different from the first time; a stereo distance measuring unit configured to acquire a first distance image from the first image and the second image and acquire a second distance image from the third image and the fourth image; and a movement amount calculating unit configured to calculate a relative movement amount between the stereo image acquiring unit and a subject between the first time and the second time on the basis of the first distance image and the second distance image.

A system for regulating fluid flow having a processor configured to reduce image noise is provided. The system includes an image sensor to capture an image of the drip chamber. The processor captures the image of the drip chamber using the image sensor, performs an edge detection on the image to generate a first processed image, and performs an AND-operation on a pixel on a first side of an axis of the first processed image with a corresponding mirror pixel on a second side of the axis of the first processed image to generate a second processed image.

This disclosure provides an image recommendation method, a client, a server, a computer system and a medium. The method includes acquiring an image, sending the acquired image to a server, such that the server extracts a scale invariant feature of the acquired image and performs retrieval of identical images according to the scale invariant feature of the acquired image, and such that the server extracts a multi-scale feature of the acquired image and performs retrieval of similar images according to the multi-scale feature of the acquired image, and receiving at least one recommended image. The at least one recommended image is based on result of the identical image retrieval and result of the similar image retrieval.

Implementations are described herein are directed to reconciling disparate orientations of multiple vision sensors deployed on a mobile robot (or other mobile vehicle) by altering orientations of the vision sensors or digital images they generate. In various implementations, this reconciliation may be performed with little or no ground truth knowledge of movement of the robot. Techniques described herein also avoid the use of visual indicia of known dimensions and/or other conventional tools for determining vision sensor orientations. Instead, techniques described herein allow vision sensor orientations to be determined and/or reconciled using less resources, and are more scalable than conventional techniques.

The disclosure provides an image processing method, an image processing apparatus, an electronic device and a storage medium, which belongs to the field of computer technologies, and specifically relates to computing vision, image processing, face recognition, and deep learning technologies in artificial intelligence. The method includes: performing skin color recognition on a face image to be processed to determine a target skin color of a face contained in the face image; obtaining a reference transformation image corresponding to the face image by processing the face image using any style transfer model in response that a style transfer model set does not comprise a style transfer model corresponding to the target skin color; and obtaining a target transformation image matching the target skin color by adjusting a hue value, a saturation value, and a lightness value of each pixel in the target region based on the target skin color.

A visual navigation inspection and obstacle avoidance method for a line inspection robot is provided. The line inspection robot is provided with a motion control system, a visual navigation system and an inspection visual system; and the method comprises the following steps: (1) according to an inspection image, the inspection visual system determining and identifying the type of a tower for inspection; (2) the visual navigation system shooting a visual navigation image in real time to obtain the type of a target object; (3) coarse positioning; (4) accurate positioning; and (5) according to the type of the tower and the type of the target object, the visual navigation system sending a corresponding obstacle crossing strategy to the motion control system, such that the inspection robot completes obstacle crossing. The inspection and obstacle avoidance method is real-time and efficient.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that generate from a first pair and a second pair of images of livestock that are within an enclosure and that are taken at different times using a stereoscopic camera, at least two distance distributions of the aquatic livestock within the enclosure. The distance distributions can be used to determine a measure associated with an optical property of the water within the enclosure. A signal associated with the measure can be provided.