An object identification and collection method is disclosed. The method includes receiving a pick-up path that identifies a route in which to guide an object-collection system over a target geographical area to pick up objects, determining a current location of the object-collection system relative to the pick-up path, and guiding the object-collection system along the pick-up path over the target geographical area based on the current location. The method further includes capturing images in a direction of movement of the object-collection system along the pick-up path, identifying a target object in the images; tracking movement of the target object through the images, determining that the target object is within range of an object picker assembly on the object-collection system based on the tracked movement of the target object, and instructing the object picker assembly to pick up the target object.

A position detector for generating 3D position information of an object in a position determination space for the object. The position detector has a camera with a lens and an image sensor that defines an imaging area with one first light deflecting element arranged in the imaging area as the camera and the at least one light deflecting element are adapted to simultaneously produce on the image sensor at least two images of the position determination space, a first image being produced by light beams deflected at the first light deflecting element, the at least two images differ with respect to the viewing direction of the position determination space.

A diagnosis support system includes a calculator configured to calculate position information indicating a positional relationship between a biological sensor and a predetermined region of a measurement target; and an extractor configured to extract, from biological information already diagnosed, biological information that is associated with position information, which is similar to the position information calculated by the calculator.

Methods, systems, and media for secure authentication of users using one or more biometric recognition systems are provided. In some embodiments, the method comprises: receiving an indication that a biometric identifier is to be used to authenticate a user to a service; receiving (i) the biometric identifier of the user from a capture device and (ii) knowledge-based secondary information associated with the user from an input device; determining a Voronoi cell identifier that corresponds to the biometric identifier; calculating a hash of the Voronoi cell identifier and the knowledge-based secondary information; transmitting the hash to a server device for verification; in response to transmitting the hash to the server device, receiving a response indicating whether the hash matches a previously stored hash that was stored in the server device; and determining whether to automatically authenticate the user to the service based on the response from the server device.

A vehicle control system for moving a vehicle to a target location is disclosed. According to examples of the disclosure, a camera captures one or more images of a known object corresponding to the target location. An on-board computer having stored thereon information about the known object can process the one or more images to determine vehicle location with respect to the known object. The system can use the vehicle's determined location and a feedback controller to move the vehicle to the target location.

Some implementations of the disclosure involve, at a device having one or more processors, one or more image sensors, and an illumination source, detecting a first attribute of an eye based on pixel differences associated with different wavelengths of light in a first image of the eye. These implementations next determine a first location associated with the first attribute in a three dimensional (3D) coordinate system based on depth information from a depth sensor. Various implementations detect a second attribute of the eye based on a glint resulting from light of the illumination source reflecting off a cornea of the eye. These implementations next determine a second location associated with the second attribute in the 3D coordinate system based on the depth information from the depth sensor, and determine a gaze direction in the 3D coordinate system based on the first location and the second location.

A first six degree-of-freedom (DoF) pose of an object from a perspective of a first image sensor is determined with a neural network. A second six DoF pose of the object from a perspective of a second image sensor is determined with the neural network. A pose offset between the first and second six DoF poses is determined. A first projection offset is determined for a first two-dimensional (2D) bounding box generated from the first six DoF pose. A second projection offset is determined for a second 2D bounding box generated from the second six DoF pose. A total offset is determined by combining the pose offset, the first projection offset, and the second projection offset. Parameters of a loss function are updated based on the total offset. The updated parameters are provided to the neural network to obtain an updated total offset.

Systems and methods are disclosed for use in electronic guidance systems for surgical navigation. A sensor is provided with an optical sensor, to provide optical information, and a measuring sensor, to provide measurements for determining a direction of gravity. The sensor communicates optical information and measurements to an inter-operative computing unit. In an embodiment, the inter-operative computing unit receives first optical information for a registration device and a patient anatomy and a measurement to determine a direction of gravity to perform a registration step. The inter-operative computing unit receives second optical information for the patient anatomy and an object and determines and presents measurements relative to the anatomy. The measurements relative to the anatomy are determined from the second optical information, and in relation to the registration of the anatomy of the patient.

An apparatus for recognizing an object in an image includes a preprocessing module configured to receive an image including an object and to output a preprocessed image by performing image enhancement processing on the received image to improve a recognition rate of the object included in the received image; and an object recognition module configured to recognize the object included in the image by inputting the preprocessed image to an input layer of an artificial neural network for object recognition.

A method for facilitating provision of food product information is provided. The method comprises providing a food package, wherein the food package is provided with a visual marker, capturing, by a camera of a user device, authentic image data depicting the visual marker, extracting marker data from the authentic image data, retrieving artificial image data linked to the marker data from an artificial image database, wherein the artificial image data depicts at least one food product component of a food product held in the food package, determining an artificial image spatial reference point based on the visual marker, generating augmented image data by combining the authentic image data, the artificial image data and the artificial image spatial reference point, providing the augmented image data to a screen of the user device.