Discrepancies between a current profile picture and a current visual appearance of the user is detected utilizing image data captured during a video teleconference, and potential updates to the user's profile picture are automatically generated and presented to the user for their consideration and selection. Additionally, for greater efficiency, an automated profile picture update process is triggerable by predetermined conditions or events, including hardware conditions, lighting or other environmental conditions, or events detected through other sensors, including concurrent audio analysis of the user during the video teleconference. A set of images, whether still pictures or live pictures, are obtained from the video information. Such an image set is initially filtered to create a smaller subset, which is then graphically modified. An image is selected and compared to an existing user profile image, with the comparison informing the generation of a user notification for choosing a new profile picture.

A system including: (a) a network hub or port adapted to detect image files in transit according to their file designations; (b) an object detector configured to identify one or more regions of interest (ROI) in each image file as potentially containing an object of interest (OOI); (c) a feature analyzer adapted to express one or more General Classification Features (GCF) of each ROI as a vector; and (d) a decision module adapted accept or reject each ROI as containing said OOI based upon the one or more GCF vectors.

An example non-transitory machine-readable storage medium includes instructions to, when executed by the processor, capture an image of a face of a user viewing a display device, identify a light source in the image, and identify light from the display device reflecting off the face of the user. The example instructions are also executable to determine a signature of the light in the image by 1) positively weighting a light measurement from the light source in the image and 2) negatively weighting a light measurement emanating from the display device and reflecting off the face of the user. The example instructions are also executable to modify a display device setting based on the signature of the light in the image.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enhancing skin tone in a ghost image are disclosed. In one aspect, a method includes the actions of receiving a color image. The actions further include converting the color image to a grayscale image. The actions further include generating a foreground image by removing background pixels from the grayscale image. The actions further include determining a foreground pixel value range of the pixel values of the foreground image. The actions further include generating a transfer function based on the foreground pixel value range, a minimum pixel value, and a maximum pixel value. The actions further include generating a transferred image by applying the transfer function to each pixel of the foreground image. The actions further include generating a monochrome image of the transferred image.

Systems and apparatuses for generating surface dimension outputs are provided. The system may collect an image from a mobile device. The system may analyze the image to determine whether they comprise one or more standardized reference objects. Based on analysis of the image and the one or more standardized reference objects, the system may determine a surface dimension output. The system may determine one or more settlement outputs and one or more repair outputs for the driver based on the surface dimension output.

System and methods for computer animations of 3D models of heads generated from images of faces is disclosed. A 2D captured image that includes an image of a face can be received and used to generate a static 3D model of a head. A rig can be fit to the static 3D model to generate an animation-ready 3D generative model. Sets of rigs can be parameters that each map to particular sounds. These mappings can be used to generate a playlists of sets of rig parameters based upon received audio content. The playlist may be played in synchronization with an audio rendition of the audio content.

An information generating apparatus includes: an information managing unit that associates and manages an image obtained by photographing skin of a person, marking information indicating one or more markings that one or more operators perform with respect to one or more characteristic parts of skin in the image, and amendment information indicating amendment that a specialist makes to the marking information; and a marking-UI processing unit that superimposes and displays the one or more markings, indicated by the marking information, and the amendment, indicated by the amendment information, on the image.

Automatic focusing where variance in the focus due to a relative shift in mounted positions of sensors is suppressed is performed. An imaging apparatus including a photometric sensor and a ranging sensor includes an image data generating unit configured to generate image data by using the photometric sensor, a detection unit configured to detect a region including an object from the image data generated by the image data generating unit, a determination unit configured to divide the image data into blocks corresponding to discretely arranged ranging points of the ranging sensor, and to determine a proportion of an area occupied by the region including the object for each block, and a focusing unit configured to focus on a ranging point of the ranging sensor corresponding to a block where the area occupied by the region including the object is at a predetermined proportion or more.

Systems and methods for detecting and tracking a marker in real time is disclosed. Shape based segmentation of at least one object detected in a first frame from a sequence of frames is performed to define a region of interest (ROI) surrounding an object of interest corresponding to the marker. A marker detection model is dynamically trained based on sampling points from a plurality of pixels in and around the ROI. The marker is then tracked in real-time based on projected ROI in subsequent frames and the trained marker detection model. To optimize computation time required in classifying the pixels as marker pixels or non-marker pixels, the ROI is reduced to half its size, classification is performed on the reduced ROI and to improve accuracy, blob detection and classifying pixels along the boundary of the reduced ROI is performed by processing the ROI in original resolution.

A video background processing system is disclosed that is configured to receive a video stream including a plurality of successive first video frames at a first resolution. The system comprises a video resolution modifier configured to reduce the resolution of the first video frames from the first resolution to a second resolution lower than the first resolution and thereby generate second video frames. The system also comprises a foreground determiner configured to determine a foreground portion and a background portion in the second video frames and to produce first foreground data indicative of locations of the foreground and background portions in the second video frames at the second resolution, wherein the foreground determiner is configured to use the first foreground data to generate second foreground data indicative of locations of the foreground and background portions in the first video frames. The system also comprises a compositor circuit configured to use replacement background content and the second foreground data to generate combined video frames at the first resolution, each combined video frame including the foreground portion from a first video frame and the replacement background content. A corresponding method is also disclosed.