A CPU acquires a distance image or a visible light image obtained by imaging a marker for measuring an SID as an object to be imaged using a TOF camera or a visible light camera. In addition, the CPU derives a marker distance between the TOF camera or the visible light camera and the marker from an image of a marker region corresponding to the marker in the acquired distance image or visible light image. Further, the CPU derives the SID on the basis of the derived marker distance and information indicating a positional relationship between an acquisition unit and the marker.

A CPU acquires a distance image or a visible light image captured by a TOF camera or a visible light camera that has, as an imageable region, a region including an irradiation region which is a space in which a breast of a subject imaged by a mammography apparatus is irradiated with radiation emitted from a radiation source and detects whether or not a foreign object other than an object to be imaged is present in the irradiation region on the basis of the distance image or the visible light image.

Methods and systems for alignment of a subject for medical imaging are disclosed, and involve providing a reference image of an anatomical region of the subject, the anatomical region comprising a target tissue, processing the reference image to generate an alignment reference image, displaying the alignment reference image concurrently with real-time video of the anatomical region, and aligning the real-time video with the alignment reference image to overlay the real-time video with the alignment reference image. Following such alignment, the subject may be imaged using, for example, fluorescence imaging, wherein the fluorescence imaging may be performed by an image acquisition assembly aligned in accordance with the alignment.

Systems and methods are provided for automatically controlling zone interactions in a three dimensional virtual environment. A computing device provides a graphical user interface (GUI) to assign zone attributes to a zone, which is a volume of space in the virtual environment. A virtual object is assigned to the zone, as well as an interaction and a responsive operation that follows the detected interaction. The virtual object's position in the virtual environment corresponds to a physical object's position in a physical environment. For example, when the computing system detects that the virtual object has entered or left the zone, according to an assigned interaction, then an assigned operation is executed to control a physical device in the physical environment.

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.

Continuous, multiple-point surveying or measurement is performed on large areas or objects. The results may be coordinated or combined with 3D localization systems or methods employing GPS, manual theodolites, range finders, laser radars or pseudolites. One disclosed example describes the use of the invention as applied to the problem of routine and repeated inspection of large aircraft, though the system and method are equally applicable to other objects with large surfaces including ships, bridges and large storage structures like tanks, buildings, and roadways.

An embodiment mobility device includes a position detector configured to detect a first current position of the mobility device, a display configured to display position information of the mobility device, and a controller configured to set the first current position of the mobility device detected by the position detector as first position information, identify an augmented reality (AR) marker in a predetermined range, based on the first position information, determine a second current position of the mobility device based on the identified AR marker, and set the second current position of the mobility device determined based on the identified AR marker as second position information, and determine final position information of the mobility device by applying the second position information to the first position information.

Various methods and systems are provided for tracking a biopsy target across one or more images. In one example, a method includes determining a position of a biopsy target in a selected image of a patient based on an image registration process with a reference image of the patient, and displaying a graphical representation of the position of the biopsy target on the selected image.

A system includes a sensor and a client. The client receives a set of frames of top-view depth images generated by the sensor. The client identifies a frame of the received frames in which a first contour associated with a first object is merged with a second contour associated with a second object. The client determines, at a first depth in the identified frame, a merged-contour region which is associated with the merged contours. The client detects a third contour at a second depth that is less than the first depth and determines a first region associated with the third contour. The client detects a fourth contour at the second depth and determines a second region associated with the fourth contour. If criteria are satisfied, the client associates the first region with a position of the first object and associates the second region with a position of the second object.

Methods, devices, and systems for identifying charging devices are provided. In one aspect, a method of identifying a charging device include: capturing an infrared image and a depth image of a current field of view with a depth camera; determining, according to the infrared image, that there are one or more suspected charging device areas that satisfy first specified conditions; determining, according to the depth image, that there is a target charging device area whose height relative to a depth camera is within a specified range in the one or more suspected charging device areas; and identifying the charging device according to the target charging device area. The first specified conditions indicate that a gray-scale value of each of pixels in an area is greater than a second specified value, and a number of the pixels in the area is greater than a third specified value.