An exemplary method includes generating a 3D mesh of a subject based on frames of time-synchronized video streams of a subject, the frames associated with a first time and generating a transformed facial-mesh model based on a facial portion of the 3D mesh and a facial-mesh model. The method further includes generating a hybrid mesh by combining the transformed facial-mesh model and at least a portion of the 3D mesh. The method further includes generating a current 3D mesh based on frames of the time-synchronized video streams associated with a second time that temporally follows the first time. The method further includes generating a deformed historical 3D mesh by applying a non-rigid deformation process to the hybrid mesh based on the current 3D mesh. The method further includes compressing the deformed historical 3D mesh to form at least one triangle-based 3D submesh including a plurality of submesh triangles.

An exemplary method includes generating a 3D mesh of a subject based on frames of time-synchronized video streams of a subject, the frames associated with a first time and generating a transformed facial-mesh model based on a facial portion of the 3D mesh and a facial-mesh model. The method further includes generating a hybrid mesh by combining the transformed facial-mesh model and at least a portion of the 3D mesh. The method further includes generating a current 3D mesh based on frames of the time-synchronized video streams associated with a second time that temporally follows the first time. The method further includes generating a deformed historical 3D mesh by applying a non-rigid deformation process to the hybrid mesh based on the current 3D mesh. The method further includes compressing the deformed historical 3D mesh to form at least one triangle-based 3D submesh including a plurality of submesh triangles.

This application discloses a target object recognition method and apparatus, a storage medium, and an electronic device. The method includes: obtaining a first image and a second image, the first image being an image obtained by shooting a target scene under visible light, and the second image being an image obtained by shooting the target scene under infrared; determining a predicted infrared intensity value corresponding to a pixel point in the first image through a prediction model; obtaining a difference between an actual infrared intensity value of a pixel point in the second image and the infrared intensity value corresponding to the pixel point at the same location in the first image; and determining a pixel point in the second image of which the difference is greater than a first threshold as a pixel point at which the target object in the target scene is located.

This application discloses a target object recognition method and apparatus, a storage medium, and an electronic device. The method includes: obtaining a first image and a second image, the first image being an image obtained by shooting a target scene under visible light, and the second image being an image obtained by shooting the target scene under infrared; determining a predicted infrared intensity value corresponding to a pixel point in the first image through a prediction model; obtaining a difference between an actual infrared intensity value of a pixel point in the second image and the infrared intensity value corresponding to the pixel point at the same location in the first image; and determining a pixel point in the second image of which the difference is greater than a first threshold as a pixel point at which the target object in the target scene is located.

Multispectral imaging and navigation systems and related techniques are provided to improve the operation of manned or unmanned mobile platforms, including mobile sensor or survey platforms. A multispectral navigation system includes a multispectral imaging system and a logic device configured to communicate with the multispectral imaging system. The multispectral imaging system includes a multispectral imaging module configured to provide multispectral image data corresponding to a projected course for a mobile platform. The logic device is configured to receive the multispectral image data, receive orientation and/or position data corresponding to the multispectral image data, and generate maneuvering obstacle information corresponding to the projected course based on the orientation and/or position data and the multispectral image data.

In order to avoid friendly fire incidents in the combat theater, novel covert identification systems and methods of identifying friendly forces are provided. The systems include at least a spectroscopic imaging device and a marker that interact with each other by using a synchronized, predetermined filter tuning sequence. The filter tuning sequence enables interacted photons to wavelength hop according to the predetermined tuning sequence. As a result, the covert identification system allows friendly forces to clearly identify each while avoiding detection by enemy forces that employ conventional broadband and night vision sensors.

In order to avoid friendly fire incidents in the combat theater, novel covert identification systems and methods of identifying friendly forces are provided. The systems include at least a spectroscopic imaging device and a marker that interact with each other by using a synchronized, predetermined filter tuning sequence. The filter tuning sequence enables interacted photons to wavelength hop according to the predetermined tuning sequence. As a result, the covert identification system allows friendly forces to clearly identify each while avoiding detection by enemy forces that employ conventional broadband and night vision sensors.

An infrastructure to vehicle communications system includes a full spectrum camera disposed on a vehicle. A sign, disposed away from the vehicle, includes a message thereon. The sign reflecting visible light, and at least a portion of the message being an optical code; the optical code not reflecting visible light and reflecting invisible light. The full spectrum camera captures the image of the sign including the optical code. A smart vision device receives the image and determines the existence of the sign from the reflected visible light and the optical code thereon from the reflected invisible light. A data base stores one or more optical codes and one or more messages associated with a respective optical code, an on board unit communicating with the database and retrieves the message as a function of the optical code, and displays the message at a display in the vehicle.

An infrastructure to vehicle communications system includes a full spectrum camera disposed on a vehicle. A sign, disposed away from the vehicle, includes a message thereon. The sign reflecting visible light, and at least a portion of the message being an optical code; the optical code not reflecting visible light and reflecting invisible light. The full spectrum camera captures the image of the sign including the optical code. A smart vision device receives the image and determines the existence of the sign from the reflected visible light and the optical code thereon from the reflected invisible light. A data base stores one or more optical codes and one or more messages associated with a respective optical code, an on board unit communicating with the database and retrieves the message as a function of the optical code, and displays the message at a display in the vehicle.

A recognition control circuitry detects a light amount of an imaging area on the basis of an image signal from a camera, a control signal from a camera control circuitry, and the like, and generates selection determination information on the basis of a detection result of the light amount. A recognition processing circuitry performs area division on an image of an imaging area generated by the camera on the basis of the selection determination information generated by the recognition control circuitry, and selects a recognizer for each area. Moreover, the recognition processing circuitry performs a subject recognition process on an image of the corresponding area by using the selected recognizer. Even when a captured image includes a bright area and a dark area, a subject in each area can be easily and accurately recognized.