Abstract: The present invention discloses system and method for processing an image. The invention processes the image by segmenting a human portrait region of the image. The invention uses ahierarchical hybrid loss module for masking the portrait region generating masked portrait region. The invention also uses data learning the masked portrait region.

Abstract: A method of motion control and textured display, comprising, receiving an image, extracting an initial mask of a subject of interest from the image, segmenting the image into the initial mask and a background, determining a color texture of the initial mask, estimating motion of the initial mask to a new mask and merging the new mask and the background into a merged image.

Abstract: A distributed light source couple-able to a mobile device, comprising, a distributed array of light emitting points and a mount connected to the distributed array and couple-able to the mobile device, the distributed array capable of light emission from a plurality of areas.

Abstract: An example method of infrared access, comprising, receiving a plurality of visual images, receiving a plurality of infrared images, calibrating pairs of at least one of the plurality of visual images to a respective at least one of the plurality of infrared images, determining an average temperature of the plurality of infrared images, determining a temperature of the respective calibrated pairs, and granting access if a visual image of the calibrated pair is authenticated by a facial recognition library and if the temperature of the calibrated pair is within a predefined threshold of the average temperature.

Abstract: A method of depth-of-field simulation, including receiving a plurality of images, predicting a layer of interest mask of the plurality of images, determining a plurality of mean brightness anchor values of a respective plurality of layers of interest window arrays, setting a plurality of layers of interest set of binary codes, determining a hamming distance between plurality of layers of interest set of binary codes, determining a cost volume based on the hamming distance, resampling a vertical cost based on a vertical ordinal direction the cost volume, resampling a horizontal cost based on a horizontal ordinal direction the cost volume, determining an all-in-focus layer based on the vertical cost and the horizontal cost, determining an out-of-focus layer based on the vertical cost and the horizontal cost and determining a depth of the all-in-focus layer and out-of-focus layer.

Abstract: The present invention discloses system and method for fake face identification. The system is a multi-spectral sensing based bio-security system. The system uses CNN module along with thermal sensors to detect human face and also detects the human temperature. The system authenticates a human face and in case of temperature generates an alarm as an alert.

Abstract: The present invention discloses system and method for processing an image. The invention processes the image by segmenting a human portrait region of the image. The invention uses ahierarchical hybrid loss module for masking the portrait region generating masked portrait region. The invention also uses data learning the masked portrait region.

Abstract: An example method of infrared access, comprising, receiving a plurality of visual images, receiving a plurality of infrared images, calibrating pairs of at least one of the plurality of visual images to a respective at least one of the plurality of infrared images, determining an average temperature of the plurality of infrared images, determining a temperature of the respective calibrated pairs, and granting access if a visual image of the calibrated pair is authenticated by a facial recognition library and if the temperature of the calibrated pair is within a predefined threshold of the average temperature.

Abstract: The present invention discloses system and method for fake face identification. The system is a multi-spectral sensing based bio-security system. The system uses CNN module along with thermal sensors to detect human face and also detects the human temperature. The system authenticates a human face and in case of temperature generates an alarm as an alert.

Abstract: A method of wheel encoder to camera calibration, including receiving a LiDAR (Light Detection and Ranging) signal, receiving a camera signal, receiving a wheel encoder signal, calibrating the camera signal to the LiDAR signal, calibrating the wheel encoder signal to the LiDAR signal and calibrating the camera signal to the wheel encoder signal based on the calibration of the camera signal to the LiDAR signal and the wheel encoder signal to the LiDAR signal.

Abstract: An example method of infrared access, comprising, receiving a plurality of visual images, receiving a plurality of infrared images, calibrating the plurality of visual images to the plurality of infrared images, determining an average temperature of the plurality of infrared images, determining an outlier temperature of an outlier infrared image of the plurality of infrared images and matching the outlier infrared image to a visual image.

Abstract: A method of depth estimation utilizing heterogeneous cameras, comprising, homogenizing a first camera image and a second camera image based on a first camera calibration dataset and a second camera calibration dataset respectively, wherein the first camera image and second camera image are distortion corrected and are zoom compensated, determining an initial image pair rectification transformation matrix of the homogenized first camera image and the homogenized second camera image, determining a delta image pair rectification transformation matrix based on the initial image pair rectification transformation matrix, determining, a final image pair rectification transformation matrix based on the initial image pair rectification transformation matrix and the delta image pair rectification transformation matrix resulting in a final rectified image pair and disparity mapping the final rectified image pair based on a depth net regression.

Abstract: A method of wheel encoder to camera calibration, including receiving a LiDAR (Light Detection and Ranging) signal, receiving a camera signal, receiving a wheel encoder signal, calibrating the camera signal to the LiDAR signal, calibrating the wheel encoder signal to the LiDAR signal and calibrating the camera signal to the wheel encoder signal based on the calibration of the camera signal to the LiDAR signal and the wheel encoder signal to the LiDAR signal.

Abstract: A method of determining a vehicle position and a vehicle velocity, including receiving a camera image sequence based on a camera borne by a vehicle and determining a camera pose based on the camera image sequence. The method includes determining a global position system location based on a global position system receiver borne by the vehicle, determining an inertial movement signal based on an inertial movement unit borne by the vehicle and receiving a wheel encoder signal from a wheel of the vehicle. The method additionally includes determining at least one of the vehicle positions and the vehicle velocity based on at least two of the camera pose, the global position system location, the inertial movement signal and the wheel encoder signal in temporal synchronization.

Abstract: A method of motion control and textured display, comprising, receiving an image, extracting an initial mask of a subject of interest from the image, segmenting the image into the initial mask and a background, determining a color texture of the initial mask, estimating motion of the initial mask to a new mask and merging the new mask and the background into a merged image.

Abstract: A method of depth-of-field simulation, including receiving a plurality of images, predicting a layer of interest mask of the plurality of images, determining a plurality of mean brightness anchor values of a respective plurality of layers of interest window arrays, setting a plurality of layers of interest set of binary codes, determining a hamming distance between plurality of layers of interest set of binary codes, determining a cost volume based on the hamming distance, resampling a vertical cost based on a vertical ordinal direction the cost volume, resampling a horizontal cost based on a horizontal ordinal direction the cost volume, determining an all-in-focus layer based on the vertical cost and the horizontal cost, determining an out-of-focus layer based on the vertical cost and the horizontal cost and determining a depth of the all-in-focus layer and out-of-focus layer.

Abstract: A distributed light source couple-able to a mobile device, comprising, a distributed array of light emitting points and a mount connected to the distributed array and couple-able to the mobile device, the distributed array capable of light emission from a plurality of areas.

Abstract: An example photographic feedback method, comprising, inputting a query image, a camera setting, a location, a temporal indicia and an environmental condition, detecting an object within the query image, projecting the location of the object, classifying the environmental condition at the location of the object, querying features of the query image of the object at the environmental condition of the projected location of the object, determining a closest image to the query image for the object at the environmental condition of the projected location of the object having a highly rated value via a cloud database and sending an updated location and at least one updated camera setting for an updated image.

Abstract: An example method of infrared access, comprising, receiving a plurality of visual images, receiving a plurality of infrared images, calibrating the plurality of visual images to the plurality of infrared images, determining an average temperature of the plurality of infrared images, determining an outlier temperature of an outlier infrared image of the plurality of infrared images and matching the outlier infrared image to a visual image.

Abstract: An example photographic feedback method, comprising, inputting a query image, a camera setting, a location, a temporal indicia and an environmental condition, detecting an object within the query image, projecting the location of the object, classifying the environmental condition at the location of the object, querying features of the query image of the object at the environmental condition of the projected location of the object, determining a closest image to the query image for the object at the environmental condition of the projected location of the object having a highly rated value via a cloud database and sending an updated location and at least one updated camera setting for an updated image.