11 results about "Camera orientation" patented technology

Embodiments here observe the driver and determine an orientation of an articulating camera based on driver gaze tracking and external object detection. A fixed camera collects image data of the vehicle's surroundings, and an articulating camera collects image data of the driver. The gaze direction is used to identify what objects in the vehicle's surroundings the driver is looking at. Based on the position of the object, an orientation of the articulating camera may be determined.

This invention provides a method, system, and device for controlling a character on a sphere's surface. A coordinate system dynamic correction module calculates the direction from the sphere's center to the character's current position in real time to determine a local ascent vector. Based on this local ascent vector, the character's rotational posture is corrected so that the character's feet always face the sphere's center, and a local coordinate system is constructed using the local ascent vector. A vector projection module acquires the camera's direction vector and performs orthogonal projection processing on it using the local coordinate system to generate a tangential movement vector parallel to the tangential plane of the ground surface. This tangential movement vector is then used to drive the character to perform displacement operations. A terrain adsorption module responds to the displacement operations by emitting a probe ray based on the local ascent vector direction determined by the local coordinate system to perform sampling processing on the ground grid, acquiring the intersection point between the probe ray and the ground grid, determining the character's target height based on the intersection point, and correcting the character's position using the target height so that the character adheres to the ground grid in real time during movement.

The application provides a scene voxelization method based on a GPU rasterizer, and relates to the technical field of real-time rendering. The method converts the spatial position of a mesh model object to a homogeneous clipping space, adopts a technology of flipping a primitive based on a maximum projection surface of the primitive to solve a voxel seam problem caused by a grazing angle formed by the primitive and a camera direction, then adopts a conservative rasterization technology of extending an edge of the primitive to solve a voxel seam problem caused by the fact that the primitive only covers a part of a voxel and does not cover a central position of the voxel, calculates an average value of all primitive information, regards all primitives covering the voxel as making equal contributions to the voxel, and introduces an access control and a data conversion operation. The improved voxelization method can meet the application scene of an electronic game and other real-time interaction rates.

This invention relates to the field of production testing equipment technology and discloses a linear laser automatic calibration system, including a base. A fixed frame, a first support frame, and a linear guide rail are fixedly mounted on the upper surface of the base. An external parameter calibration plate is disposed at the top inside the fixed frame. An internal parameter calibration plate is fixedly mounted on the side of the first support frame. A movable sub-base is movably connected to the side of the linear guide rail. A second support frame is fixedly mounted on the top of the movable sub-base. A mounting frame is fixedly mounted on the top of the second support frame. A placement seat is rotatably mounted on the inner side of the mounting frame. A camera module is disposed inside the placement seat. This invention integrates four independent checkerboard-shaped internal parameter calibration plates, allowing the camera to acquire multiple sets of data required for internal parameter calculation in a single shot, eliminating the cumbersome process of repeatedly moving the camera or calibration plate and taking 10-20 images required in traditional internal parameter calibration. Simultaneously, the linkage between the linear guide rail and the angle adjustment component allows for rapid switching of the camera orientation, achieving seamless integration of internal and external parameter calibration.

Embodiments here observe the driver and determine an orientation of an articulating camera based on driver gaze tracking and external object detection. A fixed camera collects image data of the vehicle's surroundings, and an articulating camera collects image data of the driver. The gaze direction is used to identify what objects in the vehicle's surroundings the driver is looking at. Based on the position of the object, an orientation of the articulating camera may be determined.

A computer-implemented method for determining a machine-learning function configured for taking an input 3D scene and for outputting one or more camera viewpoints each for generating a respective 2D rendering of the 3D scene. The method includes obtaining a library having 3D scenes. The method includes, based on the library, forming a first dataset for training a first neural network configured for outputting a camera position and forming a second dataset for training a second neural network configured for outputting a camera orientation. The method includes training the first neural network based on the first dataset and training the second neural network based on the second dataset. Each camera viewpoint outputted by the machine-learning function includes a camera position and a camera orientation. Such a method forms an improved solution for outputting one or more camera viewpoints of a 3D scene.

An information processing apparatus includes: a first processor that outputs, from an image of an object captured by a first camera, point information in which the imaged object is captured as a point; a second processor that outputs, from an image of the object captured by a second camera directed in a direction corresponding to the first camera, identification information that identifies the imaged object; and a third processor that associates the point information with the identification information.

Camera system (10) for the detection of an object (12), the camera system (10) comprising: - a camera (14) with variable orientation and focus, which can be aligned to a detectable object (12) such that the object (12) is at least partially located in an image field (16) of the camera (14); - a control unit (18) which is connected to the camera system (10) and is configured to: - cause the camera (14) to capture an image of the reference object located in the image field (16), wherein the reference object corresponds to a detectable object;characterized in that the control unit (18) is further configured to: - initiate object recognition based on the captured image, wherein the object recognition includes determining whether one or more optically captured objects correspond to a predetermined object type or not, wherein the object recognition based on the captured image includes edge detection in the captured image; - initiate the determination of the recognition reliability of the object recognition, wherein the recognition reliability of the object recognition denotes a reliability with which, given the prevailing quality of the received image, the object recognition based on the reference object can be successfully carried out, wherein the quality depends on the alignment and / or focus of the camera on the reference object;and- to provide information on the determined recognition reliability, which enables an assessment of the suitability of the camera's orientation and / or focus (14) for the object recognition performed, based on the determined recognition reliability, wherein- the assessment of the suitability of the camera's orientation and / or focus for the object recognition performed is limited to whether the reference object is recognized with sufficient reliability with the prevailing camera orientation and / or focus,- the assessment of the suitability of the camera's orientation and / or focus for future object recognitions is carried out during regular operation of the camera system after setup is complete;and- to provide information about the assessment of the alignment and / or focus of the camera system (10) to a user of the camera system (10) and / or a device connected to the camera system (10).

The present disclosure relates to an apparatus and a method for analyzing the static posture and dynamic motion of a body. The apparatus of the present invention comprises: an image acquisition unit for acquiring an initial image of a subject; a three-dimensional information extraction unit for extracting three-dimensional information of the subject from the initial image; a camera direction determination unit for determining a reference camera direction on the basis of posture information to be analyzed; an orthogonal image generation unit for generating an orthogonal image on the basis of the reference camera direction, the three-dimensional information, and the initial image; and a posture analysis unit for analyzing the subject's posture on the basis of the orthogonal image. According to the present invention, it is possible to analyze a posture with high accuracy even in an image captured at a short distance and to effectively analyze depth and rotation information in a three-dimensional space.

A system and method for monitoring a camera in a vehicle, the system comprising a memory and at least one processor which receives an image 6502, captured by the camera, of an interior of the vehicle, and extracts non-semantic features of the interior from the image 6504. Spatial transformation data is calculated 6506 and describes a displacement of extracted features compared with reference data, which may be determined from 3D locations within a CAD file, describing reference features of the interior when the camera is in a reference orientation. An orientation of the camera relative to the reference orientation is calculated based on the spatial transformation data 6508. Optionally, the extracting comprises segmenting the image based on a mask applied to the image, and extracting based on the segmented image. Also provided is a non-transitory computer-readable device having instructions stored thereon for implementing the method. The system allows for calibration of the camera. [Fig. 65]

A method for mapping camera locations and camera fields of view (FOV) of surveillance cameras in a facility. The installation location and FOV are identified for each camera, defined by the installation location, horizontal orientation, vertical tilt, and optical specifications. A camera map representing the cameras can be generated, where nodes identify the distance and orientation between adjacent cameras. This map is distributed to the cameras, enabling autonomous neighbor identification. When an object of interest moves toward the FOV of an adjacent camera, a peer command is sent to track the object. Camera locations can be identified using mobile devices via manual map selection or WiFi / Bluetooth beacons. Camera orientation can be determined using the alignment of the mobile device with the camera lens or using the camera IMU output for image stabilization.