A wearable electronic device includes a left-eye display configured to output light of a first color corresponding to a 3D left-eye image, a right-eye display configured to output light of a second color corresponding to a 3D right-eye image, a left-eye optical waveguide configured to adjust a path of the light of the first color and output the light of the first color, a right-eye optical waveguide configured to adjust a path of the light of the second color and output the light of the second color, a left-eye display control circuit configured to supply a driving power and a control signal to the left-eye display, a right-eye display control circuit configured to supply a driving power and a control signal to the right-eye display, a communication module configured to communicate with a mobile electronic device, and a second control circuit configured to supply a driving power and a control signal to the communication module.

An information processing apparatus includes: a plurality of stereo cameras arranged so that directions of baseline lengths of the stereo cameras intersect each other; a depth estimation unit that estimates, from captured images captured by the plurality of stereo cameras, a depth of an object included in the captured images; and an object detection unit that detects the object based on the depth estimated by the depth estimation unit and reliability of the depth, the reliability being determined in accordance with an angle of a direction of an edge line of the object with respect to the directions of the baseline lengths of the plurality of stereo cameras.

A method for acquiring a distance from a moving body to an object located in any direction of the moving body includes steps of: an image processing device (a) instructing a sweep network to project pixels of images, generated by cameras covering all directions of the moving body, onto main virtual geometries and apply 3D concatenation operation thereon to generate an initial 4D cost volume, (b) generating a final main 3D cost volume therefrom through a cost volume computation network, and (c) generating sub inverse distance indices corresponding to inverse values of sub separation distances between a sub reference point and sub virtual geometries, and main inverse distance indices corresponding to inverse values of main separation distances between a main reference point and the main virtual geometries, by using a sub cost volume and the final main 3D cost volume, to thereby acquire the distance to the object.

Disclosed is a cross-view image optimizing method and apparatus, and a computer equipment and a readable storage medium. The method includes: acquiring a sample image and a pre-trained cross-view image generating model; generating an multi-dimensional cross-view image of the sample image by a multi-dimensional feature extracting module of the first generator to obtain dimension features and cross-view initial images at multiple dimensions; obtaining a multi-dimensional feature map with corresponding dimension features by the second generator; inputting the multi-dimensional feature map to a multi-channel attention module of the second generator for feature extraction and calculating a feature weight of each attention channel, obtaining attention feature images, attention images and feature weights in a preset number of the attention channels; and weighting and summing the attention images and the attention feature images of all the channels according to the feature weights, and obtaining a cross-view target image.

Described are methods for identifying the in-field positions of plant features on a plant by plant basis. These positions are determined based on images captured as a vehicle (e.g., tractor, sprayer, etc.) including one or more cameras travels through the field along a row of crops. The in-field positions of the plant features are useful for a variety of purposes including, for example, generating three-dimensional data models of plants growing in the field, assessing plant growth and phenotypic features, determining what kinds of treatments to apply including both where to apply the treatments and how much, determining whether to remove weeds or other undesirable plants, and so on.

A processing device generates composite images from a sequence of images. The composite images may be used as frames of video. A foreground/background segmentation is performed at selected frames to extract a plurality of foreground object images depicting a foreground object at different locations as it moves across a scene. The foreground object images are stored to a foreground object list. The foreground object images in the foreground object list are overlaid onto subsequent video frames that follow the respective frames from which they were extracted, thereby generating a composite video.

Methods and devices for manipulating an image are described. The method comprises receiving image data, the image data including a first image obtained from a first camera and a second image obtained from a second camera, the first camera and the second camera being oriented in a common direction; identifying one or more boundaries of an object in the image data by analyzing the first image and the second image; and displaying a manipulated image based on the image data, wherein the manipulated image includes manipulation of at least a portion of the first image based on boundaries of the object.

A stereoscopic picture generating apparatus comprising: a storage unit to get stored with a first image containing partial images and a second image containing partial images corresponding respectively to the partial images contained in the first image; and an arithmetic unit to extract a first position defined as an existing position of a first partial image contained in the first image and a second position defined as an existing position of a second partial image contained in the first image, to calculate a first differential quantity defined as a difference between the first position and the second position, to calculate a third position defined as a new existing position of a third partial image contained in the second image that corresponds to the first partial image based on the first differential quantity, and to generate a third image based on the third position of the third partial image.

Methods and systems for generating stereoscopic content with granular control over binocular disparity based on multi-perspective imaging from representations of light fields are provided. The stereoscopic content is computed as piecewise continuous cuts through a representation of a light field, minimizing an energy reflecting prescribed parameters such as depth budget, maximum binocular disparity gradient, desired stereoscopic baseline. The methods and systems may be used for efficient and flexible stereoscopic post-processing, such as reducing excessive binocular disparity while preserving perceived depth or retargeting of already captured scenes to various view settings. Moreover, such methods and systems are highly useful for content creation in the context of multi-view autostereoscopic displays and provide a novel conceptual approach to stereoscopic image processing and post-production.

An automatic range finding method is applied to measure a distance between a stereo camera and a reference plane. The automatic range finding method includes acquiring a disparity-map video by the stereo camera facing the reference plane, analyzing the disparity-map video to generate a depth histogram, selecting a pixel group having an amount greater than a threshold from the depth histogram, calculating the distance between the stereo camera and the reference plane by weight transformation of the pixel group, and applying a coarse-to-fine computation for the disparity-map video.