Systems and methods for eye image set selection, eye image collection, and eye image combination are described. Embodiments of the systems and methods for eye image set selection can include comparing a determined image quality metric with an image quality threshold to identify an eye image passing an image quality threshold, and selecting, from a plurality of eye images, a set of eye images that passes the image quality threshold.

A localization and mapping method is for localizing and mapping a moving apparatus in a moving process. The localization and mapping method includes an image capturing step, a feature point extracting step, a flag object identifying step, and a localizing and mapping step. The image capturing step includes capturing an image frame at a time point of a plurality of time points in the moving process by a camera unit. The flag object identifying step includes identifying whether the image frame includes a flag object among a plurality of the feature points in accordance with a flag database. The flag database includes a plurality of dynamic objects, and the flag object is corresponding to one of the dynamic objects. The localizing and mapping step includes performing localization and mapping in accordance with the image frames captured and the flag object thereof in the moving process.

A method for controlling a robotic device is presented. The method includes positioning the robotic device within a task environment. The method also includes mapping descriptors of a task image of a scene in the task environment to a teaching image of a teaching environment. The method further includes defining a relative transform between the task image and the teaching image based on the mapping. Furthermore, the method includes updating parameters of a set of parameterized behaviors based on the relative transform to perform a task corresponding to the teaching image.

An image fusion system provides a predicted alignment between images of different modalities and synchronization of the alignment, once acquired. A spatial tracker detects and tracks a position and orientation of an imaging device within an environment. A predicted pose of an anatomical feature can be determined, based on previously acquired image data, with respect to a desired position and orientation of the imaging device. When the imaging device is moved into the desired position and orientation, a relationship is established between the pose of the anatomical feature in the image data and the pose of the anatomical feature imaged by the imaging device. Based on tracking information provided by the spatial tracker, the relationship is maintained even when the imaging device moves to various positions during a procedure.

A computer-readable medium storing contents configured to cause a computing device to obtain image data describing a subject, measure the subject based on the obtained image data to obtain one or more spatial dimensions, and access data describing a wearable item based on the spatial dimensions of the subject.

The technology relates to cargo vehicles. National, regional and/or local regulations set requirements for operating cargo vehicles, including how to distribute and secure cargo, and how often the cargo should be inspected during a trip. However, such regulations have been focused on traditional human-driven vehicles. Aspects of the technology address various issues involved with securement and inspection of cargo before a trip, as well as monitoring during the trip so that corrective action may be taken as warranted. For instance, imagery and other sensor information may be used to enable proper securement of cargo before starting a trip. Onboard sensors along the vehicle monitor the cargo and securement devices/systems during the trip to identify issues as they arise. Such information is used by the onboard autonomous driving system (or a human driver) to take corrective action depending on the nature of the issue.

A pure pose solution method and system for a multi-view camera pose and scene are provided. The method includes: a pure rotation recognition (PRR) step: performing PRR on all views, and marking views having a pure rotation abnormality, to obtain marked views and non-marked views; a global translation linear (GTL) calculation step: selecting one of the non-marked views as a reference view, constructing a constraint t.sub.r=0, constructing a GTL constraint, solving a global translation (I), reconstructing a global translation of the marked views according to t.sub.r and (I), and screening out a correct solution of the global translation; and a structure analytical reconstruction (SAR) step: performing analytical reconstruction on coordinates of all 3D points according to a correct solution of a global pose. The method and system can greatly improve the computational efficiency and robustness of the multi-view camera pose and scene structure reconstruction.

Disclosed are an image synthesis method and a related apparatus, the method includes: determining a target area on a preview image by means of eyeball tracking technology; on the basis of brightness parameters of the target area, determining multiple exposure parameter sets; setting a camera module with the multiple exposure parameter sets to acquire multiple reference images, each reference image corresponding to a different exposure parameter set; and synthesizing the multiple reference images to obtain a target image.

An image display method includes: obtaining a homography matrix between a first target plane and a second target plane according to the first target plane and the second target plane; obtaining a target displacement according to the homography matrix and an attitude; obtaining a target pose according to the target displacement, the target pose including a position and an attitude of a camera coordinate system of a current frame image in a world coordinate system; and displaying an AR image according to the target pose.

The present disclosure relates to methods and apparatus for display processing. For example, disclosed techniques facilitate region of interest tracking for in-motion frames. Aspects of the present disclosure can identify a layer of interest of a plurality of layers associated with a frame. Aspects of the present disclosure can also determine coordinates for a region of interest based on characteristics associated with the identified layer of interest. Further, aspects of the present disclosure can perform display processing on the region of interest of the frame based on the coordinates for the region of interest.