Abstract: A method for predicting color variance using a proxy includes generating a first 3D object proxy based on a stored 3D object, generating a second 3D object proxy based on the stored 3D object, transforming the first 3D object proxy based on a 3D object identified in a frame of a video, transforming the second 3D object proxy based on the 3D object identified in a key frame of the video, mapping color attributes from the 3D object identified in the frame of the video to the transformed first 3D object proxy, mapping color attributes from the 3D object identified in the key frame to the transformed second 3D object proxy, and generating color data for the 3D object based on the color attributes for the transformed first 3D object proxy and the color attributes for the transformed second 3D object proxy.

Abstract: The invention provides a system, apparatus and method for providing remote and rapid access to image data. The invention can be employed during surgery to enable health care personnel, located away from a location where the surgery is being performed, to view and evaluate tissue excised from a patient during the surgery. Such health care personnel can provide feedback to the surgeon during the surgery, to enhance an outcome of the surgery.

Abstract: Compressing a frame of video includes receiving a frame of a video, identifying a three dimensional (3D) object in the frame, matching the 3D object to a stored 3D object, compressing the frame of the video using a color prediction scheme based on the 3D object and the stored 3D object, and storing the compressed frame with metadata, the metadata identifying the 3D object, indicating a position of the 3D object in the frame of the video and indicating an orientation of the 3D object in the frame of the video.

Abstract: The invention provides a system, apparatus and method for providing remote and rapid access to image data. The invention can be employed during surgery to enable health care personnel, located away from a location where the surgery is being performed, to view and evaluate tissue excised from a patient during the surgery. Such health care personnel can provide feedback to the surgeon to enhance an outcome of the surgery.

Abstract: Approaches presented herein provide systems and methods for determining duplicate objects within an interaction environment. Connectivity information for an object may be used to map a set of three linearly independent vectors corresponding to a transform applied to the object. These three linearly independent vectors may be used to form canonical forms of first and second objects to determine whether the first object and the second object are duplicates or near-duplicates. Copies of duplicate or near-duplicate objects may then be deleted from the interaction environment and represented by a common object to which one or more additional transforms are applied.

Abstract: Techniques and systems are disclosed for using swept volume profile data cached in association with a PRM to improve various aspects of motion planning for a robot. In some implementations, a first probabilistic road map representing possible paths to be travelled by a robot within a physical area is generated. An initial path for the robot within the first probabilistic road map is determined. Data indicating a second probabilistic road map representing a path to be travelled by a movable object within the physical area is obtained. A potential obstruction associated with one or more edges included in the subset of edges is detected. An adjusted path for the robot within the first probabilistic road map is then determined based on the potential obstruction.

Abstract: Techniques of compressing level of detail (LOD) data involve sharing a texture image LOD among different mesh LODs for single-rate encoding. That is, a first texture image LOD corresponding to a first mesh LOD may be derived by refining a second texture image LOD corresponding to a second mesh LOD. This sharing is possible when texture atlases of LOD meshes are compatible.

Abstract: Techniques and systems are disclosed for using swept volume profile data cached in association with a PRM to improve various aspects of motion planning for a robot. In some implementations, a first probabilistic road map representing possible paths to be travelled by a robot within a physical area is generated. An initial path for the robot within the first probabilistic road map is determined. Data indicating a second probabilistic road map representing a path to be travelled by a movable object within the physical area is obtained. A potential obstruction associated with one or more edges included in the subset of edges is detected. An adjusted path for the robot within the first probabilistic road map is then determined based on the potential obstruction.

Abstract: Techniques of compressing triangular mesh data involve generating a neighborhood table (i.e., a table) of fixed size that represents a neighborhood of a predicted vertex of a triangle within a triangular mesh for input into a machine-learning (ML) engine. For example, such a neighborhood table as input into a ML engine can output a prediction for a value (e.g., a position) of a vertex. The residual between the prediction and the actual value of the vertex is stored in an array. The data in the array representing the residuals may be compressed and transmitted over a network. Upon receipt by a computer, the array may be decompressed by the computer. Obtaining the actual value involves the receiving computer generating the same neighborhood table, inputting that neighborhood table into the same ML engine to produce the predicted value, and adding the predicted value to the residual from the decompressed file.

Abstract: Techniques of compressing level of detail (LOD) data involve sharing a texture image LOD among different mesh LODs for single-rate encoding. That is, a first texture image LOD corresponding to a first mesh LOD may be derived by refining a second texture image LOD corresponding to a second mesh LOD. This sharing is possible when texture atlases of LOD meshes are compatible.

Abstract: Techniques of compressing triangular mesh data involve generating a neighborhood table (i.e., a table) of fixed size that represents a neighborhood of a predicted vertex of a triangle within a triangular mesh for input into a machine-learning (ML) engine. For example, such a neighborhood table as input into a ML engine can output a prediction for a value (e.g., a position) of a vertex. The residual between the prediction and the actual value of the vertex is stored in an array. The data in the array representing the residuals may be compressed and transmitted over a network. Upon receipt by a computer, the array may be decompressed by the computer. Obtaining the actual value involves the receiving computer generating the same neighborhood table, inputting that neighborhood table into the same ML engine to produce the predicted value, and adding the predicted value to the residual from the decompressed file.

Abstract: The invention provides a system, apparatus and method for providing remote and rapid access to image data. The invention can be employed during surgery to enable health care personnel, located away from a location where the surgery is being performed, to view and evaluate tissue excised from a patient during the surgery. Such health care personnel can provide feedback to the surgeon to enhance an outcome of the surgery.

Abstract: Compressing a frame of video includes receiving a frame of a video, identifying a three dimensional (3D) object in the frame, matching the 3D object to a stored 3D object, compressing the frame of the video using a color prediction scheme based on the 3D object and the stored 3D object, and storing the compressed frame with metadata, the metadata identifying the 3D object, indicating a position of the 3D object in the frame of the video and indicating an orientation of the 3D object in the frame of the video.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network including an encoder network and decoder network and configured to receive a network input that includes sensor data characterizing a deformable object and to process the network input to generate a network output that specifies a mesh of the deformable object. Once trained, the neural network can be deployed in a robotic system for use in allowing a motion planner to issue timely commands which adjust a currently planned motion according to the mesh in order to prevent any collision between the robot and the deformable object.

Abstract: Compressing a frame of video includes receiving a frame of a video, identifying a three dimensional (3D) object in the frame, matching the 3D object to a stored 3D object, compressing the frame of the video using a color prediction scheme based on the 3D object and the stored 3D object, and storing the compressed frame with metadata, the metadata identifying the 3D object, indicating a position of the 3D object in the frame of the video and indicating an orientation of the 3D object in the frame of the video.

Abstract: Techniques of compressing level of detail (LOD) data involve generating a codec that can perform progressive refinement on a single rate decoded LOD. Nevertheless, by generating a small amount of extra information in a single rate decoded LOD, a progressive refiner can use the information provided in the single rate decoded LOD to refine the LOD. For example, in some implementations, the extra information is a corner of a face of a mesh; the progressive decoder may then begin traversal of the mesh from that corner for refinement. It is noted that the single rate decoded LODs are able to be refined by the same refinement information as the progressively decoded LODs.

Abstract: Techniques of compressing level of detail (LOD) data involve defining a cost metric that predicts how much computing resources are necessary to decode and render a mesh at a given LOD. The cost metric may be optimized by a selection of a LOD reduction process of a plurality of processes at each LOD reduction step. For each process of the plurality of processes, the LOD is reduced according to that process and the resulting reduced LOD is evaluated according to the cost metric. Each such process at that LOD reduction step produces a respective LOD, which includes a mesh, one or more texture atlases, and/or other attributes. The LOD produced by the process having the lowest value of the cost metric at a reduction step is the LOD that is input into the next LOD reduction step.

Abstract: Techniques of compressing triangular mesh data involve encoding a bitstream that defines a traversal order for vertices in a triangular mesh. The encoded bitstream defining the traversal order is in addition to an encoded bitstream of prediction errors and is an explicit, rather than implicit, traversal. One example of a bitstream that defines a traversal order is an array in which a bit signifies whether a step in an implicit, deterministic scheme such as a depth-first traversal. Upon decoding, the usual deterministic steps are used to find the vertices of the triangular mesh unless specified by the traversal bitstream. Such an encoded bitstream, when occupying less memory than that saved from the compression efficiencies gained in defining the traversal order defined in the bitstream, offers a simple, efficient compression without requiring that the triangular mesh be connected.

Abstract: A system, apparatus and method and method for controlling interoperation between a resonant scanner and a movable stage. The movable stage being employed to position a specimen for optical scanning by the resonant scanner. The invention providing high resolution scanning of specimen tissue at a rate of ten times or more faster than other known methods of optically scanning a specimen.

Abstract: A method includes receiving geometric data to be encoded, generating a signature for the geometric data based on the at least one property associated with the geometric data, enumerating a set of first options, enumerating a set of second options, encoding the geometric data using the enumerated first option and the enumerated second option, decoding the encoded geometric data, selecting one of the enumerated second options based on a cost function, and training a classifier based on the signature, the enumerated first option and the selected second option.