Methods and apparatus for determining and/or using the image date, e.g., image capture date, of one or more scanned images based on image content is described. In various embodiments at least one object, e.g., face of a person, is identified in an image. The age of the object is determined, e.g., using age estimation techniques. The determined, e.g., estimated, age of the identified face is then compared to stored face age to image capture date information. Such information is obtained or derived from other images with known capture dates and including an image of the same object, e.g., face, as the image with the unknown date. Based on the estimated object age and stored information associating object age to image capture date, the image date, e.g., image capture date of the scanned image is determined. This information is then used to organize storage of the image with other images.

Systems and methods employing unique optics, combined with data gathering techniques that capture user interaction in the system at the point of engagement and point of entry. This facilitates gathering real time data on users, customers or other people during engagement with elements of the system to provide analytics in real time.

A method of determining a cosmetic skin attribute of a person is provided. The method includes obtaining a color channel image of a person's skin, analyzing the color channel image with a computer using entropy statistics to obtain an entropy value, and then determining a cosmetic skin attribute for the person based on the entropy value.

This disclosure relates generally to methods and systems for predicting wait time of queues at service area such as market places including retail stores and super markets. The present methods and systems accurately predicts the wait times of the plurality of queues by utilizing various visual cues of the customers, along with the number of service items and the efficiency of the service operator. The visual cues including a demographic factor such as age, gender, ethnicity of the customer and a senti-motional factor such as sentiments including positive attitude or negative attitude and emotions of the customers including happy state, sad state, and irritation state of the customer. The customers may choose the queue having least predicted wait time and may take informed decision hoping for faster check-out, based on the predicted wait times of the queues. Hence, customer experience and customer satisfaction may be achieved.

Provided are an image processing apparatus, an image processing method, an image processing program, and a recording medium that stores the program, capable of finding images of different persons captured in the same age. An image is specified as a first image, a user in the image is recognized as a first person, and an age thereof is estimated. An image is specified as a second image, a user in the image is recognized as a second person, and an age thereof is estimated. In a case where the user recognized as the first person and the user recognized as the second person are not the same person and a difference between the age of the user and the age of the user is within a range of a threshold value, the first image and the second image are detected as an image combination.

A method and system may use machine learning analysis of audio data to automatically identify a user's biometric characteristics. A user's client computing device may capture audio of the user. Feature data may be extracted from the audio and applied to statistical models for determining several biometric characteristics. The determined biometric characteristic values may be used to identify individual health scores and the individual health scores may be combined to generate an overall health score and longevity metric. An indication of the user's biometric characteristics which may include the overall health score and longevity metric may be displayed on the user's client computing device.

A method of age and gender estimation, comprising receiving an input image, detecting a facial image within the input image, estimating a head pose based on a set of facial image intensities of the facial image, wherein the head pose is expressed as a yaw, a pitch and a roll, determining whether the yaw, the pitch and the roll of the head pose is less than a predetermined threshold, aligning the facial image if the yaw, the pitch and the roll of the head pose are less than the predetermined threshold and predicting an age and a gender of the aligned facial image.

A system for non-invasive estimation of dementia progression. The system includes a computer device and a server. The computer device obtains an image of a subject's head from at least one angle. The server and/or computer device includes a plurality of machine learning models configured to: analyze the image for patterns related to dementia symptoms; and estimate progress of said dementia symptoms of said subject based on the analysis. The server and/or computer device pre-processes the image by performing a plurality of pre-processing steps comprising: importing the image; detecting eyes and shape of the head based on a previously trained machine learning model; rotating the image based on detection of the eyes and shape of the head; normalizing the image to one standard.

The present disclosure provides a temperature correcting method, apparatus and system, which relates to the technical field of computers. The method includes: acquiring a target reference image-frame pair containing a person, wherein the target reference image-frame pair includes a target visible-light image frame and a target thermal-imaging image frame; converting the target visible-light image frame into a depth image frame; inputting the depth image frame and the target thermal-imaging image frame into an atmosphere-inverse-scattering model, wherein the atmosphere-inverse-scattering model refers to a neural network model obtained by fitting a relation between depths and temperature correcting values in advance; and by using the atmosphere-inverse-scattering model, based on the depth image frame, performing temperature correction to the target thermal-imaging image frame, to obtain a target temperature. The present disclosure may effectively increase the accuracy of person temperature measurement.

A method for monitoring and controlling usage of a remote work computing device is provided. The work computing device is in communication with a first computing device over a network, and comprises a display including a field of view (FOV) and a camera directed at the FOV. The method comprises: providing a first memory for storing a feature/attribute of an unauthorized object; capturing a digital image using the camera including a first object in the FOV; identifying a feature/attribute of the first object; and comparing the feature/attribute of the first object with the feature/attribute of the unauthorized object. When the feature/attribute of the first object matches the feature/attribute of the unauthorized object, a notification is communicated to the first computing device including the captured digital image, the display is prevented from being viewed from the FOV, and/or a task manager window is captured and communicated to the first computing device.