Provided is an object recognition method which includes obtaining a first visible-light image acquired by the first camera device and a second visible-light image acquired by the second camera device; performing exposure processing on the first visible-light image according to the luminance information of the bright area image of the first visible-light image and performing exposure processing on the second visible-light image according to the luminance information of the dark area images of the first visible-light image and/or the second visible-light image, where the dark area image is an area image having a luminance value less than or equal to the preset value; and performing target object detection on the first visible-light image obtained after exposure processing and the second visible-light image obtained after exposure processing and recognizing and verifying a target object according to the detection result.

Facial biometric systems and methods employ digital fingerprints that represent facial characteristics. These systems and methods may perform various digital fingerprint related processes including induction (acquiring of the facial data, generation of a digital fingerprint and storing in a database) and authentication (a process of using the digital fingerprint of the face to perform biometrics). The facial biometric system and method combines these processes with a particular set of hardware to perform the facial biometrics process that is novel and provides benefits and capabilities not achievable by other biometric systems and methods.

A digital story includes textual, visual, and/or audio aspects. Generation of a new digital story and/or editing of an existing digital story can include, for instance, coordinating presentation of textual, visual, and/or audio aspects of the digital story. A digital story can be viewed and/or accessed by a user remote from one or more authors of the digital story.

Systems for detecting when a person exhibits a smile with therapeutic benefits including a facial expression detection device and a system processor. The facial expression detection device is configured to acquire facial expression data. The system processor is in data communication with the facial expression detection device and is configured to execute stored computer executable system instructions. The computer executable system instructions include the steps of receiving facial expression parameter data establishing target facial expression criteria, receiving current facial expression data from the facial expression detection device, comparing the current facial expression data to the target facial expression criteria of the facial expression parameter data, and identifying whether the current facial expression data satisfies the target facial expression criteria. The target facial expression criteria define a smile with therapeutic benefits.

Systems, methods and devices are for optical imaging are described. A system includes a light source and a light detection unit. The light source includes a light-emitting device and a first spectral filter opposite the light emitting device. The first spectral filter includes at least one dielectric filter and has a first angular dependence of a transmission passband. The light source further includes at least one reflector adjacent side surfaces of the light emitting device. The light detection unit includes an optical sensor and a second spectral filter opposite the optical sensor. The second spatial filter has a second angular dependence of a transmission passband that is matched to the first angular dependence.

The present disclosure provides a video image composition method including the following steps. A priority level list is obtained, and the priority level list includes multiple priority levels of multiple person identities. Multiple video streams are received. Multiple identity labels corresponding to human face frame images from the video streams are determined. The multiple display levels of the human face frame images are determined according to the identity labels and priority level list. A part of the human face frame images being in speaking status are detected. At least one of the part of the human face frame images being in speaking status is constituted as a main display area of a video image, according to the display levels.

Exemplary embodiments include a computer-implemented method of training a neural network for facial reconstruction including collecting a set of 3D head scans, combining each feature of each 3D head scan with a weight to create a modified set of 3D head scans, training the neural network using the modified set of head scans, and inputting a real digital facial image into the neural network for facial reconstruction. Further exemplary embodiments include the set of 3D head scans comprising approximately a tenth or less in quantity in comparison to a quantity of the modified set of 3D head scans. The modified set of 3D head scans may comprise features found in the set of 3D head scans or the modified set of 3D head scans may consist of features found in the set of 3D head scans.

A system can determine, from a video of an online session, respective bounding boxes of text names of people, wherein the text names are presented in the video, and wherein images of the people are present in the video. The system can determine, from the video, respective faces of the people. The system can associate a first bounding box of the bounding boxes with a first face of the faces based on the first bounding box satisfying a function of distance with respect to the first face among the faces. The system can extract a name from the first bounding box via optical character recognition. The system can extract a subportion of the video that comprises the first face. The system can store an association between the name and the subportion of the video that comprises the first face.

An information processing apparatus includes a controller configured to generate an avatar of a user as a 3D object based on a user image of the user. The controller is configured to acquire a new image of the user, generate an excluded image by excluding a portion from the new image, and update the avatar of the user by rendering the excluded image in overlap with at least a portion of the user image.

Disclosed are a face image and iris image acquisition method and device, a computer-readable readable storage medium and an apparatus. The method includes rotating the first tripod head to force the face lens and the iris lens to be in acquisition positions; capturing a first face image and a first iris image simultaneously by the face lens and the iris lens; and locating the iris in the first iris image, and if no iris is located, determining whether a condition of light-avoiding rotation is satisfied, and if the condition is satisfied, rotating the second tripod head to adjust an angle or a position of the supplementary light source to enable a light spot region to avoid an iris region.