Methods and systems for the use of detected objects for image processing are described. A computing device autonomously controlling a vehicle may receive images of the environment surrounding the vehicle from an image-capture device coupled to the vehicle. In order to process the images, the computing device may receive information indicating characteristics of objects in the images from one or more sources coupled to the vehicle. Examples of sources may include RADAR, LIDAR, a map, sensors, a global positioning system (GPS), or other cameras. The computing device may use the information indicating characteristics of the objects to process received images, including determining the approximate locations of objects within the images. Further, while processing the image, the computing device may use information from sources to determine portions of the image to focus upon that may allow the computing device to determine a control strategy based on portions of the image.

An object detector and a sensing apparatus are provided. The object detector includes a light source, a light deflector configured to deflect light emitted from the light source, and a photodetector configured to detect the light that is deflected by the light deflector and then is reflected at an object, where the light deflector includes a plurality of reflection planes that rotate on a rotation axis, the reflection planes are oblique to the rotation axis and are rotationally symmetrical about the rotation axis, and the light that is emitted from the light source enters the light deflector in a direction parallel to the rotation axis. The sensing apparatus includes the object detector, and a monitoring controller configured to determine whether an object is present, and obtain movement information of the object including at least one of moving direction and moving speed of the object.

A moving amount estimating apparatus includes a position data obtaining unit, a first estimating unit, and a second estimating unit. The position data obtaining unit obtains a plurality of position data used to form a projection object image before and after movement of a mobile body. The first estimating unit calculates a moving amount of a parallel movement and/or a rotational movement of second position data as a moving amount of a mobile body when a plurality of moving position data is calculated. A second estimating unit compensates for a wheel moving amount based on a comparison between a second reference moving amount based on a rotating amount of a wheel during a predetermined period and a first reference moving amount obtained by calculating the moving amount of the mobile body in the first estimating unit during the predetermined period, and estimates the moving amount of the mobile body.

Systems, apparatuses, and methods are provided for developing a fingerprint database and selecting feature geometries for determining the geographic location of a device. A device collects a depth map at a location in a path network. Two-dimensional feature geometries from the depth map are extracted using a processor of the device. The extracted feature geometries are ranked to provide ranking values for the extracted feature geometries. A portion of the extracted feature geometries are selected based upon the ranking values and a geographic distribution of the extracted feature geometries.

A method for measuring distance and areas by mobile devices combined with light beam projectors that combines a mobile device with a light beam projector which projects the light beams in the direction identical to the one of the image retrieved from a photodetector module of the mobile device, so as to project a first measuring point and a second measuring point and produce a first distance and a second distance, and then calculate the moving coordinates of the first and second measuring points with a first azimuth data and a second azimuth date detected by an azimuth sensor of the mobile device. Thus the method would be able to calculate the coordinate distance between the first and second measuring points, even the area surrounded by the coordinate distance, the first distance, and the second distance. In other words, the method can calculate the coordinate distance between any two points and the measure of the area surrounded thereby, achieving a convenient and augmented effectiveness in the measuring process.

An object-detection system for an automated vehicle includes an object-detector, a digital-map, and a controller. The object-detector is used to observe a field-of-view proximate to a host-vehicle. The digital-map is used to indicate a roadway-characteristic proximate to the host-vehicle. The controller is configured to define a region-of-interest within the field-of-view based on the roadway-characteristic, and preferentially-process information from the object-detector that corresponds to the region-of-interest.

A method for compressing geometric data and video is disclosed. The method includes receiving video and associated geometric data for a physical location, generating a background video from the video, and generating background geometric data for the geometric data outside of a predetermined distance from a capture point for the video as a skybox sphere at a non-parallax distance. The method further includes generating a geometric shape for a first detected object within the predetermined distance from the capture point from the geometric data, generating shape textures for the geometric shape from the video, and encoding the background video and shape textures as compressed video along with the geometric shape and the background geometric data as encoded volumetric video.

An imaging sensor system, having a view of a target area comprising: a rigid mount unit having at least two imaging sensors disposed within the mount unit, wherein a first imaging and a second imaging sensor each has a focal axis passing through an aperture in the mount unit, wherein the first imaging sensor generates a first image area comprising a first data array of pixels and the second imaging sensor generates a second image area comprising a second data array of pixels, wherein the first and second imaging sensors are offset to have a first image overlap area in the target area, wherein the first sensors image data bisects the second sensors image data in the first image overlap area.

When there are no customers in a store, a laser is scanned along an aisle between product shelving units installed in the store, and if that laser is reflected midway in the optical path, it is determined that there is an object in the sensing range according to the laser. The determination result is then notified to a user by a site that corresponds to the position where the laser has been reflected being marked in a layout image that represents the product shelving units, displayed on a terminal device.

A method of operating an obstacle data model construction system of an aircraft is provided. With a vehicle moving through a vehicle obstacle space from a first to a second position, the method includes scanning the vehicle obstacle space at the first and second positions, generating first and second boundary data sets from results of the scanning at the first and second positions, respectively, and deriving first and second shrouded regions from the first and second boundary data sets, respectively. The method further includes identifying a high confidence occupancy region from intersecting portions of the first and second shrouded regions or identifying an occupancy region from a union of the first and second shrouded regions.