Techniques are disclosed for providing a notification that a person is at a particular location. For example, a resident device may receive from a user device an image that shows a face of a first person, the image being captured by a first camera of the user device. The resident device may also receive, from another device having a second camera, a second image showing a portion of a face of a second person, the second camera having a viewable area showing a particular location. The resident device may determine a score indicating a level of similarity between a first set of characteristics associated with the face of the first person and a second set of characteristics associated with the face of a second person. The resident device may then provide to the user device a notification based on determining the score.

The present invention relates to a face recognition method and a face recognition device, the method including: a step for detecting one or more faces in an image frame; a step for updating a face object in a face list by using the one or more pieces of detected face information; and a step for recognizing an identity corresponding to the face object by using a plurality of feature vectors of the face object in the updated face list.

Disguised Face Identification (DFI) system and method for identifying multiple individuals with disguised faces in uncontrolled environments/scenarios is provided. The Disguised Face Identification (DFI) system and method includes detecting facial landmarks/facial key-points and performing face identification using the ScatterNet Hybrid Deep Learning (SHDL) Network. The system also can be evolved, after deployment, by the user as it provides one with an ability to add new faces to a known face database which are identified by the system thereafter. Further includes two facial disguise (FG) datasets, the datasets are simple facial disguise (FG) datasets and complex facial disguise (FG) datasets for training the deep convolutional networks.

A media application segments a library of media associated with a user account into episodes, wherein each episode is associated with a corresponding time period. The media application generates, using an event machine-learning model, an event signal that indicates a likelihood that an event occurred in each episode, wherein the event machine-learning model is a classifier that receives the media as input. The media application generates an event significance score for each episode. The media application determines one or more events from the episodes based on the event signal and a corresponding event significance score exceeding a threshold event significance value. The media application provides a user interface that includes corresponding media from the one or more events.

Various embodiments of a facial recognition system are provided. In one embodiment, a processor determines a value for a lighting parameter associated with a captured facial image, determines whether any previously obtained images in a biometric database includes a similar value for the lighting parameter and, if not, stores the newly captured image in the database along with the lighting parameter value. In another embodiment, the processor calculates a score indicative of the likelihood that the face in the captured facial image is identical to the face of a previously obtained image in the database, determines whether the score exceeds a threshold value and, if so, generates a signal indicating a match. The processor adjusts the threshold based on one or more parameter values.

Face image data is acquired and a face image is captured, and a difference between a face image indicated by the face image data and the face image that is captured or a candidate of the difference is detected on the basis of at least one of the face image indicated by the face image data that is acquired, and the face image that is captured. Guidance is acquired on the basis of the difference or the candidate of the difference which is detected, and an output unit is controlled to output the guidance.

A computer vision processor of a camera extracts attributes of persons or vehicles from hyperzooms generated from image frames. The hyperzooms represent traffic patterns. The extracting is performed using a feature extractor of an on-camera convolutional neural network (CNN) including an inverted residual structure. The attributes include at least colors of clothing of the persons or colors of the vehicles. Mobile semantic segmentation models of the CNN are generated using the hyperzooms and the attributes. Attribute analytics are generated by executing the mobile semantic segmentation models while obviating network usage by the camera. The attribute analytics are stored in a key-value database located on a memory card of the camera. A query is received from the server instance specifying one or more of the attributes. The attribute analytics are filtered using the one or more of the attributes to obtain a portion of the traffic patterns.

A gate device is provided which prevents unauthenticated users from passing. The gate device is provided with an acquisition unit, an authentication request unit, a determination unit and a gate control unit. The acquisition unit acquires biological information of a person to be authenticated who is in an authentication area. The authentication request unit transmits to a server device an authentication request that contains the acquired biological information. The determination unit detects a person approaching the local gate device by using a sensor for detecting approaching persons, and determines whether or not the approaching person and the person to be authenticated are the same person. If authentication by the server device is successful and the approaching person and the authenticated person are the same person, then the gate control unit controls the gate to allow passage of the authenticated person.

A sanitization system for a space includes an ultraviolet (UV) light source configured to emit UV light towards a UV light zone at a UV light level, a motion sensor device configured to sense movements of one or more individuals, and a controller. The controller is configured to determine, based on the movements of the one or more individuals, an exposure parameter value for each of the one or more individuals in the UV light zone, determine that the value of the exposure parameter determined for at least one of the one or more individuals exceeds a threshold value, and, responsive to determining that the value of the exposure parameter determined for the at least one of the one or more individuals exceeds the threshold value, cause the UV light source to reduce the UV light level of the UV light emitted towards the UV light zone.

A method for reducing the number of images or the length of a video from a digital image collection using a social network, includes receiving a digital image collection captured by a user to be viewed by a viewer; wherein the viewer and the user are members of the same social network and using a processor to access the social network to determine a relationship between a viewer and the user. The method further includes using the processor to determine a set of summarization parameters based on the relationship between the viewer and the user and using the processor to reduce the number of images or the length of the video from the digital image collection using the determined set of summarization parameters to be viewed by the viewer.