A camera module including a lighting unit configured to output an incident light signal to be emitted to an object, a lens unit configured to concentrate a reflected light signal reflected from the object, an image sensor unit configured to generate electric signals from the reflected light signal concentrated by the lens unit, a tilting unit configured to shift an optical path of at least one of the incident light signal and the reflected light signal for each image frame in units of subpixels of the image sensor unit, and an image control unit configured to extract depth information of the object using a phase difference between the incident light signal and the reflected light signal. The image control unit includes an image controller configured to extract the depth information having a higher resolution than a plurality of subframes generated using the electric signals on the basis of the subframes.

Systems and methods are provided performing for low compute depth map generation by implementing acts of obtaining a stereo pair of images of a scene, downsampling the stereo pair of images, generating a depth map by stereo matching the downsampled stereo pair of images, and generating an upsampled depth map based on the depth map using an edge-preserving filter for obtaining at least some data of at least one image of the stereo pair of images.

Systems and methods are provided performing for low compute depth map generation by implementing acts of obtaining a stereo pair of images of a scene, downsampling the stereo pair of images, generating a depth map by stereo matching the downsampled stereo pair of images, and generating an upsampled depth map based on the depth map using an edge-preserving filter for obtaining at least some data of at least one image of the stereo pair of images.

Described herein are systems and methods for structure scan using an unmanned aerial vehicle. For example, some methods include accessing a three-dimensional map of a structure; generating facets based on the three-dimensional map, wherein the facets are respectively a polygon on a plane in three-dimensional space that is fit to a subset of the points in the three-dimensional map; generating a scan plan based on the facets, wherein the scan plan includes a sequence of poses for an unmanned aerial vehicle to assume to enable capture, using image sensors of the unmanned aerial vehicle, of images of the structure; causing the unmanned aerial vehicle to fly to assume a pose corresponding to one of the sequence of poses of the scan plan; and capturing one or more images of the structure from the pose.

Described herein are systems for roof scan using an unmanned aerial vehicle. For example, some methods include capturing, using an unmanned aerial vehicle, an overview image of a roof of a building from above the roof; presenting a suggested bounding polygon overlaid on the overview image to a user; determining a bounding polygon based on the suggested bounding polygon and user edits; based on the bounding polygon, determining a flight path including a sequence of poses of the unmanned aerial vehicle with respective fields of view at a fixed height that collectively cover the bounding polygon; fly the unmanned aerial vehicle to a sequence of scan poses with horizontal positions matching respective poses of the flight path and vertical positions determined to maintain a consistent distance above the roof; and scanning the roof from the sequence of scan poses to generate a three-dimensional map of the roof

An information display system includes a frame, a pair of cameras arranged at both side ends of the frame, a transparent display fitted into the frame, a display position setting device that detects a target based on a feature extracted from image data captured by the pair of cameras, and sets, as a display position, a position at which a straight line connecting an eye of a user wearing the frame and the target passes through the transparent display, and a controller that controls the transparent display in such a way as to display a point light at the display position set by the display position setting device.

Described herein are apparatuses, systems and methods for generating an interactive three-dimensional (“3D”) environment using virtual depth. A method comprises receiving a pre-rendered media file comprising a plurality of frames, receiving depth data related to the media file, wherein the depth data corresponds to each of the plurality of frames, creating an invisible three-dimensional (“3D”) framework of a first frame of the media file based on the corresponding depth data, and rendering a new first frame in real time to include the pre-rendered first frame, one or more virtual visible 3D objects and the invisible 3D framework.

Described herein are apparatuses, systems and methods for generating an interactive three-dimensional (“3D”) environment using virtual depth. A method comprises receiving a pre-rendered media file comprising a plurality of frames, receiving depth data related to the media file, wherein the depth data corresponds to each of the plurality of frames, creating an invisible three-dimensional (“3D”) framework of a first frame of the media file based on the corresponding depth data, and rendering a new first frame in real time to include the pre-rendered first frame, one or more virtual visible 3D objects and the invisible 3D framework.

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.

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.