An estimation device includes a memory and at least one processor. The at least one processor is configured to acquire information regarding a target object. The at least one processor is configured to estimate information regarding a location and a posture of a gripper relating to where the gripper is able to grasp the target object. The estimation is based on an output of a neural model having as an input the information regarding the target object. The estimated information regarding the posture includes information capable of expressing a rotation angle around a plurality of axes.

A system and method for localizing an autonomous vehicle using a digital stereo camera mounted to the autonomous vehicle and oriented to obtain images of the road surface. The system comprises an image processor configured to analyze the images of the road surface and identify micro-features, such as pores, holes, cracks, and granular material embedded in the street. The image processor is configured to compile previously obtained images of the road surface into reference mosaics and to compare the micro-features identified in newly obtained images to the reference mosaic to determine the location of the autonomous vehicle. The system may be further configured with a communications module to transmit images and localization information to a database repository or server.

Methods and systems for determining a displacement of a peripheral device are provided. In one example, a peripheral device comprises: an image sensor, and a hardware processor configured to: control the image sensor to capture a first image of a surface when the peripheral device is at a first location on the surface, the first image comprising a feature of the first location of the surface; execute a trained machine learning model using data derived from the first image to estimate a displacement of the feature between the first image and a reference image captured at a second location of the surface; and determine a displacement of the peripheral device based on the estimated displacement of the feature.

Disclosed are systems and methods for mapping multiple views to an identity. The systems and methods may include receiving a plurality of images that depict an object. Attributes associated with the object may be extracted from the plurality of images. An identity of the object may be determined based on processing the attributes.

Embodiments describe a method for positioning a hinged vehicle including a primary part and a secondary part coupled to the primary part at a project site. The method includes receiving, from an image capturing device, digital image data representing one or more features of the secondary part; performing image analysis on the digital image data to identify positions of the one or more features of the secondary part; identifying an angle of at least a portion of the secondary part; calculating a current position of the secondary part based on the angle; calculating a positional difference between a correct position at the project site for the secondary part and a current position of the secondary part at the project site; and initiating a change in a position of the primary part to compensate for the positional difference and to position the secondary part on the correct position.

The system, devices and methods herein enable autonomous and tele-operation of tele-operated robots for maintenance of a property around known and unknown obstacles. A method may include using an unmanned aerial vehicle for obtaining additional data relating to the property and obstacles within the property and plan a path around the obstacles using data from sensors on-board the tele-operated robot and the aerial image. A method may also provide optimization of total time needed for performing the property maintenance and the labor costs in situations where manual intervention is needed for navigating the tele-operated robot around obstacles on the property or for removing obstacles on the property.

A method can include identifying a geolocation of an object in an image, the method comprising receiving data indicating a pixel coordinate of the image selected by a user, identifying a data point in a targetable three-dimensional (3D) data set corresponding to the selected pixel coordinate, and providing a 3D location of the identified data point.

Disclosed herein is an apparatus for the real-time monitoring of construction objects. The apparatus for the real-time monitoring of construction objects includes: a communication unit configured to receive image data acquired by photographing a construction site, and to transmit safety information to an external device; and a monitoring unit provided with a prediction model pre-trained using binary image sequences of construction objects at the construction site as training data, and configured to detect a plurality of construction objects from image frames included in image data received via the communication unit and convert the detected construction objects into binary images, to generate future frames by inputting the resulting binary images to the prediction model, and to derive proximity between the construction objects by comparing the generated future frames with the resulting binary images and generate the safety information.

Methods and systems for image processing are provided. Image data may be obtained. The image data may include a plurality of voxels corresponding to a first plurality of ribs of an object. A first plurality of seed points may be identified for the first plurality of ribs. The first plurality of identified seed points may be labelled to obtain labelled seed points. A connected domain of a target rib of the first plurality of ribs may be determined based on at least one rib segmentation algorithm. A labelled target rib may be obtained by labelling, based on a hit-or-miss operation, the connected domain of the target rib, wherein the hit-or-miss operation may be performed using the labelled seed points to hit the connected domain of the target rib.

Processing for judging whether a face is included in a frame is performed, in a predetermined interval, on each of frames included in a moving image of a subject, displayed on a monitor, until the judgment becomes positive. If it is judged that a face is included in a frame, the facial position is detected in the frame, and stored. Then, judgment is made as to whether a face is included in the next frame after predetermined time. If the judgment is positive, the facial position is detected. The previously stored facial position is replaced by the newly detected facial position, and the newly detected facial position is stored. These processes are repeated until photographing operation is performed by operating a release unit.