An antenna adjustment device and an antenna adjustment method for a mobile vehicle, in which main structure includes the mobile vehicle having a directional antenna, a photographic element and an epipolar line analysis component. The epipolar line analysis component establishes data connection with the directional antenna and the photographic element. The photographic element includes a photographic part and an image receiving processing part. With the above structure, the user can use the photographic element with the directional antenna to define an epipolar line of optimal connection efficiency with the base station on the image receiving processing part. When the connection is needed, the mobile vehicle is moved for adjusting an image of the base station imaged by the image receiving processing part to align to the epipolar line, so as to get the optimal connection efficiency.

An apparatus comprises a first interface for receiving a plurality of partially overlapping images of an object from a corresponding plurality of cameras being arranged along a first and a second direction according to a camera pattern. The apparatus comprises an analyzing unit configured for selecting at least one corresponding reference point in an overlap area of a set of images, and for determining displacement information along the first and the second direction of the reference point in each of the other images of the set of images. A misalignment of the plurality of images along the first and the second direction is compensated by the displacement information so as to obtain aligned images. The apparatus comprises a determining unit configured for determining offset information between principal points of the plurality of cameras using at least three aligned images. The apparatus comprises a second interface for providing calibration data based on the displacement information and based on the offset information. The calibration data allows for calibrating the plurality of images so as to comply to the camera pattern.

Provided is a three-dimensional reconstruction method of reconstructing a three-dimensional model from multi-view images. The method includes: selecting two frames from the multi-view images; calculating image information of each of the two frames; selecting a method of calculating corresponding keypoints in the two frames, according to the image information; and calculating the corresponding keypoints using the method of calculating corresponding keypoints selected in the selecting of the method of calculating corresponding keypoints.

Disclosed are methods, systems, and non-transitory computer-readable medium for analysis of images including wearable items. For example, a method may include obtaining a first set of images, each of the first set of images depicting a product; obtaining a first set of labels associated with the first set of images; training an image segmentation neural network based on the first set of images and the first set of labels; obtaining a second set of images, each of the second set of images depicting a known product; obtaining a second set of labels associated with the second set of images; training an image classification neural network based on the second set of images and the second set of labels; receiving a query image depicting a product that is not yet identified; and performing image segmentation of the query image and identifying the product in the image by performing image analysis.

Provided is a position detection unit configured to detect position information of a first imaging device and a second imaging device on the basis of corresponding characteristic points from a first characteristic point detected as a physical characteristic point regarding a subject imaged by the first imaging device, and a second characteristic point detected as a physical characteristic point regarding the subject imaged by the second imaging device. The present technology can be applied to an information processing apparatus that specifies positions of a plurality of imaging devices.

A method and system for determining the location of objects using a plurality of full motion video cameras where the location is based on the intersecting portions of a plurality of three-dimensional shapes that are generated from the video data provided by the cameras. The three-dimensional shapes include two-dimensional shapes that contain predetermined traits in each of the frames of the video signals.

An apparatus comprises a first interface for receiving a plurality of partially overlapping images of an object from a corresponding plurality of cameras being arranged along a first and a second direction according to a camera pattern. The apparatus comprises an analyzing unit configured for selecting at least one corresponding reference point in an overlap area of a set of images, and for determining displacement information along the first and the second direction of the reference point in each of the other images of the set of images. A misalignment of the plurality of images along the first and the second direction is compensated by the displacement information so as to obtain aligned images. The apparatus comprises a determining unit configured for determining offset information between principal points of the plurality of cameras using at least three aligned images. The apparatus comprises a second interface for providing calibration data based on the displacement information and based on the offset information. The calibration data allows for calibrating the plurality of images so as to comply to the camera pattern.

The invention relates to a device for recognising distance in real time including first and second cameras. The device also includes a third camera arranged nearer the first camera than the second camera. The first, second and third cameras acquire simultaneously first, second and third images respectively. The device also includes an electronic circuit that estimates the distance of an object as a function of a stereoscopic correspondence established between the first and second elements representative of the object and belonging to the first and second images respectively. The stereoscopic correspondence is established by taking into account a relationship between the first elements and corresponding third elements belonging to the third image.

There is provided a computer implemented method for generating a three dimensional (3D) image based of fluorescent illumination, comprising: receiving in parallel by each of at least three imaging sensors positioned at a respective parallax towards an object having a plurality of regions with fluorescent illumination therein, a respective sequence of a plurality of images including fluorescent illumination of the plurality of regions, each of the plurality of images separated by an interval of time; analyzing the respective sequences, to create a volume-dataset indicative of the depth of each respective region of the plurality of regions; and generating a 3D image according to the volume-dataset.

The present invention relates to a method and apparatus for classifying images of solar battery cells. The method according to an exemplary embodiment of the present invention is performed by an electronic apparatus, and is a method for determining whether a solar battery cell being inspected is defective, based on an electroluminescence (EL) image of the solar battery cell being inspected. The method comprises: a step of classifying an EL image of a solar battery cell being inspected, according to whether a black spot occupies a certain percentage or more of the EL image of the solar battery cell being inspected, namely, primarily classifying the EL image of the solar battery cell being inspected into a first type in which a black spot occupies a certain percentage or more, or a second type in which a black spot occupies less than the certain percentage; and a step of secondarily classifying the type of defect of the solar battery cell being inspected, based on the EL image of the solar battery cell being inspected, by using a pre-trained defect classification model, if the EL image of the solar battery cell being inspected is primarily classified into the first type.