A computer-implemented method is provided. The method includes classifying a video clip of consecutive video frames into one of predefined new classes in relation to a base training set class. The method further includes controlling a system of a motor vehicle for accident avoidance responsive to the one of the predefined classes indicating an impending collision. The classifying step includes extracting video frame features from the video clip. The classifying step further includes aggregating the video frame features of the consecutive video frames into a single frame feature to form a video level feature presentation. The classifying step also includes mapping, by a distance-based classifier, the video level feature presentation into a classification prediction based on cosine similarity.

An electronic device and an operating method of the electronic device are provided. The electronic device includes: a communication interface comprising communication circuitry, a memory storing one or more instructions, and a processor, when executing the one or more instructions stored in the memory, is configured to: while content is executed, identify an execution condition of the content, select a frame-processing mode between an image quality-preference mode and an input lag-preference mode, based on the identifying of the execution condition, the image quality-preference mode being a frame-processing mode in which processing is performed by taking into account image quality of the content preferentially to an input lag of the content, and the input lag-preference mode being a frame-processing mode in which processing is performed by taking into account the input lag of the content preferentially to the image quality of the content, and perform image-quality processing on frames of the content based on the selected frame-processing mode.

Described herein is a system and computer implemented method for finding similars for a selected clothing image amongst a set of clothing images in an electronic catalog in an online store serving online customers. An object detection model is applied to extract the clothing section within the clothing images to create a preprocessed image. A first machine learning model is applied on the preprocessed image(s) to convert the colors and textures of said preprocessed image into a first set of vector representations. A second machine learning model is applied on the preprocessed image(s) to convert the shapes of said preprocessed image into a second set of vector representations. Operations of mapping nearest vectors, matching attributes, sorting and ranking are performed, and thereafter similar images are displayed to the online customer.

A system and method for de-identification of an image may include receiving an input image of a human face; iteratively modifying the input image to produce an output image of the human face until: (a) a threshold indicating how unlikely a human is to associate the input image with the output image is reached, and (b) a threshold indicating an ability of a computerized unit to associate the input image with the output image is reached; and providing the output image.

Provided is an object detection device which can detect with high accuracy a symmetrical target object represented in an image. The object detection device includes a memory which stores a model pattern representing a plurality of predetermined features in different positions to each other on a target object when the target object is viewed from a predetermined direction, a feature extraction unit which extracts a plurality of the predetermined features from an image in which the target object is represented, and a collation unit which calculates a degree of coincidence representing a degree of matching between the plurality of the predetermined features of the model pattern and a plurality of the predetermined features extracted from a region corresponding to the model pattern in the image while changing at least one of a relative position or angle, or a relative direction and relative size of the model pattern with respect to the image, and which judges that the target object is represented in the region of the image corresponding to the model pattern when the degree of coincidence is equal to or greater than a predetermined threshold, wherein the predetermined features stored in the memory include a feature of interest which can be used for detecting a position in a specific direction of the target object in the image or which can be used for detecting an angle in a rotational direction centered about a predetermined point of the target object in the image, and the collation unit increases the contribution in the calculation of the degree of coincidence when the feature of interest of the model pattern and a predetermined feature in the image match as compared to the case in which a predetermined feature of the model pattern other than the feature of interest and the predetermined feature in the image match to calculate the degree of coincidence.

An acquisition unit (15a) detects an operation event of a user to acquire an occurrence position of the operation event in an operation screen and a captured image of the operation screen. An extraction unit (15b) extracts images that are able to become candidates for a GUI part from the acquired captured image, identifies which image the operation event has occurred on from the occurrence position of the operation event, and records an occurrence clock time of the operation event and the identified image in an associated manner. A classification unit (15c) classifies a group of recorded images into clusters in accordance with similarities of the images. A determination unit (15d) adds up the number of times the operation event has occurred in the images for each classified cluster, and in a case in which the aggregated value is equal to or greater than a predetermined threshold value, determines an image included in the cluster as an image of the GUI part that is an operation target at the occurrence clock time of the operation event.

[Object] To provide a display apparatus, an image generation method, and a program that are capable of displaying images such that an image displayed on a display unit and a scene outside the display apparatus appear to be continuous.

[Solving Means] The display apparatus includes a first image sensor, a first distance sensor, a second sensor, a display unit, and an image generation unit. The first image sensor is disposed on a first surface side of an apparatus main body. The first distance sensor is disposed on the first surface side. The second sensor is disposed on a second surface side opposite to the first surface side. The display unit is disposed on the second surface side. The image generation unit generates a display image to be displayed on the display unit, using a two-dimensional image of a subject and a distance image of the subject, the two-dimensional image being acquired by the first image sensor, the distance image being acquired by the first distance sensor, on the basis of three-dimensional position information of a viewpoint of a photographer, the three-dimensional position information being calculated on the basis of a sensing result acquired by the second sensor.

A method for performing biometric recognition in a system in which biometric information is distributed and stored in a plurality of databases includes extracting biometric information of a user, generating a plurality of biometric information segments by dividing the extracted biometric information, calculating distances between pre-stored biometric information template segments for each of the plurality of databases and a corresponding one of the plurality of biometric information segments, and detecting a biometric information template matching the biometric information by using the calculated distances.

Model data of a virtual model imitating an object model is generated based on photographed data obtained by photographing the object model including a joint structure. A given applied joint structure is applied to the virtual model. The virtual model based on the model data is disposed in a given virtual space. Virtual model management data including the model data and data of the applied joint structure is stored in a predetermined storage section or is externally output as data for causing a joint of the virtual model to function.

An image processing device is an image processing device configured to cause a display to display three-dimensional data as a three-dimensional image, the three-dimensional data representing a biological tissue. The image processing device includes: a control unit configured to detect a series of positions of a catheter inserted into the biological tissue from data obtained in time series by a sensor observing the surrounding of a lumen of the biological tissue while moving in the lumen, and to switch a display mode between a first mode for displaying a first figure representing the series of positions in the three-dimensional image, and a second mode for displaying a second figure representing one position among the series of positions in the three-dimensional image.