Abstract:
A system and method for generating photo-realistic talking-head animation from a text input utilizes an audio-visual unit selection process. The lip-synchronization is obtained by optimally selecting and concatenating variable-length video units of the mouth area. The unit selection process utilizes the acoustic data to determine the target costs for the candidate images and utilizes the visual data to determine the concatenation costs. The image database is prepared in a hierarchical fashion, including high-level features (such as a full 3D modeling of the head, geometric size and position of elements) and pixel-based, low-level features (such as a PCA-based metric for labeling the various feature bitmaps).
Abstract:
A method for modeling three-dimensional objects to create photo-realistic animations using a data-driven approach. The three-dimensional object is defined by a set of separate three-dimensional planes, each plane enclosing an area of the object that undergoes visual changes during animation. Recorded video is used to create bitmap data to populate a database for each three-dimensional plane. The video is analyzed in terms of both rigid movements (changes in pose) and plastic deformation (changes in expression) to create the bitmaps. The modeling is particularly well-suited for animations of a human face, where an audio track generated by a text-to-speech synthesizer can be added to the animation to create a photo-realistic “talking head”.
Abstract:
A method for tracking heads and faces is disclosed wherein a variety of different representation models can be used to define individual heads and facial features in a multi-channel capable tracking algorithm. The representation models generated by the channels during a sequence of frames are ultimately combined into a representation comprising a highly robust and accurate tracked output. In a preferred embodiment, the method conducts an initial overview procedure to establish the optimal tracking strategy to be used in light of the particular characteristics of the tracking application.
Abstract:
A method and systems for cloud-based digital pathology include scanning received slides that include a pathology sample to produce a sample image in a shared memory, analyzing the sample image using one or more execution nodes, each including one or more processors, according to one or more analysis types to produce intermediate results, transmitting some or all of the sample image to a client device, further analyzing the sample image responsive to a request from the client device to produce a final analysis based on the intermediate results, and transmitting the final analysis to the client device.
Abstract:
Methods and systems for digital pathology with low-latency analytics include determining potential regions of interest within an image in accordance with one or more high-priority analyses, dividing the potential regions of interest into a plurality of sub-sections optimized for parallel computation, analyzing the sub-sections using one or more execution nodes, each including one or more processors, using a copy of the image stored in a shared memory according to the one or more high-priority analyses, and storing an intermediate analysis result based on analysis results from the one or more execution nodes in a shared memory.
Abstract:
Methods and systems for interactive image analysis include receiving a selection of a region of an image and a request for analysis of the selection at an interface layer, transferring the selection and the request to an interpretation layer for analysis, dividing the selected region of the image into a plurality of sub-sections optimized for parallel computation to provide an analysis result that minimizes perceptible delay between receiving the request and receipt of results, analyzing the sub-sections using one or more execution nodes using a copy of the image stored in a shared memory, and providing combined analysis results to the interface layer for display.
Abstract:
A method system for training an apparatus to recognize a pattern includes providing the apparatus with a host processor executing steps of a machine learning process; providing the apparatus with an accelerator including at least two processors; inputting training pattern data into the host processor; determining coefficient changes in the machine learning process with the host processor using the training pattern data; transferring the training data to the accelerator; determining kernel dot-products with the at least two processors of the accelerator using the training data; and transferring the dot-products back to the host processor.
Abstract:
Systems and methods for extracting a radial contour around a given point in an image includes providing an image including a point about which a radial contour is to be extracted around. A plurality of directions around the point and a plurality of radius lengths for each direction are provided. Local costs are determined for all radius lengths for each direction by comparing texture variances at each radius length with the texture variance at a further radius length. A radius length is determined, using a processor, for each direction based on the accumulated value of the local costs to provide a radial contour.
Abstract:
A method for measuring structural entropy of cell nuclei in a histological micrograph of a biopsy tissue sample involves the steps of: obtaining a dye color map from a color image of the biopsy tissue sample; locating cell nuclei in the dye color map; and measuring structural features within small groups (cliques or paths) of cell nuclei to determine their degree of organization (or structural entropy). Also, an apparatus for measuring structural entropy of cell nuclei in a histological micrograph of a biopsy tissue sample includes a processor executing instructions for: obtaining a dye color map of the biopsy tissue sample; locating cell nuclei in the dye color map; and measuring structural features within small groups (cliques or paths) of cell nuclei to determine their degree of organization (or structural entropy).
Abstract:
A method of improving the lighting conditions of a real scene or video sequence. Digitally generated light is added to a scene for video conferencing over telecommunication networks. A virtual illumination equation takes into account light attenuation, lambertian and specular reflection. An image of an object is captured, a virtual light source illuminates the object within the image. In addition, the object can be the head of the user. The position of the head of the user is dynamically tracked so that an three-dimensional model is generated which is representative of the head of the user. Synthetic light is applied to a position on the model to form an illuminated model.