A face identification system detects that a user is wearing a facemask, by finding an area on the face image which has no facial recognition facial features, and that area is a continuous area and includes the nose and mouth of the user, being covered by the mask. Responsive to making this detection, the system determines that the user is wearing a facemask and carries out a facemask recognition operation. The facemask recognition operation can include finding some other way to verify the user, or reducing security so that the user can be verified while still wearing the facemask.

In an approach to identifying occluded objects, a computer retrieves a first image that includes an object at least partially occluded by one or more occlusions. A computer removes the one or more occlusions from the first image to create a partial object in a second image. A computer runs a detection model with the second image to predict one or more identifications of a symbol represented by the partial object. A computer determines top predictions of the one or more identifications of the symbol by the detection model. A computer identifies at least one geometric property associated with the one or more identifications of the symbol included in the one or more top predictions. A computer applies the at least one geometric property to the partial object. A computer determines a probability of the one or more top predictions correctly identifying the symbol represented by the partial object.

Disclosed herein are methods, apparatus, and systems for iris recognition. A method includes acquiring at least two angularly differentiated iris images from a subject needing access, processing each of the at least two angularly differentiated iris images to generate at least one boundary delineated image from one of the at least two angularly differentiated iris images, applying image comparative analysis to the at least two angularly differentiated iris images to generate a boundary delineated image when the processing fails to produce the at least one boundary delineated image, segmenting and encoding one of the at least one boundary delineated image or the boundary delineated image to generate at least one iris template, matching the at least one iris template against an enrolled iris, and accepting the subject for access processing when the at least one iris template matches the enrolled iris.

The present disclosure describes systems, non-transitory computer-readable media, and methods for accurately and efficiently removing objects from digital images taken from a camera viewfinder stream. For example, the disclosed systems access digital images from a camera viewfinder stream in connection with an undesired moving object depicted in the digital images. The disclosed systems generate a temporal window of the digital images concatenated with binary masks indicating the undesired moving object in each digital image. The disclosed systems further utilizes a 3D to 2D generator as part of a 3D to 2D generative adversarial neural network in connection with the temporal window to generate a target digital image with the region associated with the undesired moving object in-painted. In at least one embodiment, the disclosed systems provide the target digital image to a camera viewfinder display to show a user how a future digital photograph will look without the undesired moving object.

A method of accessing real-time body-camera/wearable recording device video/footage and audio in two-way communication with the wearer. The technologies herein will also describe a method of transferring/synchronizing the data on the camera flash storage to a cloud storage account. The data in the cloud storage account can be accessed by departmental heads and viewed in relatively close sequence of the original capture thereof. This will safeguard against any data destruction on the physical camera storage, the potentiality of the device being stolen, lost, or intentional deletes, etc. Subsequently, the technologies herein can be used to triangulate the device(s) location via pings (5G cellular service) and/or satellite positioning. The technologies herein can be adapted to automated surveillance drones, remotely controlled drones, and/or robotic drones in the personification of humans/animals, nontraditional/traditional forms or a variant thereof.

A method of barrier detection in an imaging controller includes: obtaining an image of a support structure configured to support a plurality of items on a support surface extending between a shelf edge and a shelf back; extracting frequency components representing pixels of the image; based on the extracted frequency components, identifying a barrier region of the image, the barrier region containing a barrier adjacent to the shelf edge; and detecting at least one empty sub-region within the barrier region, wherein the empty sub-region is free of items between the barrier and the shelf back.

Video conferencing systems are popular means for remote parties to interact in real-time. A user may wish to emphasize certain visual elements of the video conference, for example, a company's logo or the contents of a whiteboard may be important to remain clearly seen by the viewers of the video conference. As elements are obscured, a previously captured image of the obscured visual element may be overlaid on top of the obscuring image to visual remove the obscuring object. Additionally, certain visual elements may be enhanced, such that a small visual element may appear larger or clearer within the video image.

Provided according to one embodiment of the present invention is a method for controlling a robot cleaner, comprising: a map data collection step of collecting first information collected by photographing a cleaning target area by means of a depth camera and second information collected by photographing the cleaning target area by means of an IR sensor; a depth data filtering step of removing, from the first information, information which is determined to be noise when detecting obstacles; and a data restoration step of, if there is a lost part of the information on the obstacles by comparing the second information with the information that is determined to be noise and removed in the depth data filtering step, restoring the lost part. According to the present embodiment, it is possible to obtain effective obstacle information by removing noise that is not removed despite filtering of the depth camera, so as to detect even thin obstacles.

A method and device for identifying a state, electronic device and computer-readable storage medium are provided. The method includes: acquiring a to-be-detected image for a specific scene and determining a region of interest in the to-be-detected image; the region of interest being a region obtained by subtracting an occlusion range of the storage container in a closed state from an occlusion range in an open state; determining a positional relation between the region of interest and specific object regions where the specific objects are positioned in the to-be-detected image; determining at least one value based on values of pixels in the region of interest, when the positional relation represents that there is no specific object region partially overlapping the region of interest; and determining whether the storage container is in an open state or closed state based on the at least one value and a preset value range.

In variants, the method for automatic debris detection includes: determining a region image; optionally determining a parcel representation for the region image; generating a debris representation using the region image; generating a debris score based on the debris representation; and optionally monitoring the debris score over time.