Abstract:
Disclosed are a method and device for transmitting a panoramic video. The method includes: requesting a server for acquiring a first panoramic video file; and upon detecting a change in a viewing angle of a user, according to an FOV type of the first panoramic video file, requesting the server for acquiring a second panoramic video file or an auxiliary FOV video file of the first panoramic video file.
Abstract:
Objects within two-dimensional video data are modeled by three-dimensional models as a function of object type and motion through manually calibrating a two-dimensional image to the three spatial dimensions of a three-dimensional modeling cube. Calibrated three-dimensional locations of an object in motion in the two-dimensional image field of view of a video data input are determined and used to determine a heading direction of the object as a function of the camera calibration and determined movement between the determined three-dimensional locations. The two-dimensional object image is replaced in the video data input with an object-type three-dimensional polygonal model having a projected bounding box that best matches a bounding box of an image blob, the model oriented in the determined heading direction. The bounding box of the replacing model is then scaled to fit the object image blob bounding box, and rendered with extracted image features.
Abstract:
Scenes reconstruction may be performed using videos that capture the scenes at high resolution and frame rate. Scene reconstruction may be associated with determining camera orientation and/or location (“camera pose”) throughout the video, three-dimensional coordinates of feature points detected in frames of the video, and/or other information. Individual videos may have multiple frames. Feature points may be detected in, and tracked over, the frames. Estimations of camera pose may be made for individual subsets of frames. One or more estimations of camera pose may be determined as fixed estimations. The estimated camera poses for the frames included in the subsets of frames may be updated based on the fixed estimations. Camera pose for frames not included in the subsets of frames may be determined to provide globally consistent camera poses and three-dimensional coordinates for feature points of the video.
Abstract:
A method of producing a stereo image from a temporal sequence of digital images, comprising: receiving a temporal sequence of digital images; analyzing pairs of digital images to produce corresponding stereo suitability scores, wherein the stereo suitability score for a particular pair of images is determined responsive to the relative positions of corresponding features in the particular pair of digital image; selecting a pair of digital images including a first image and a second image based on the stereo suitability scores; using a processor to analyze the selected pair of digital images to produce a motion consistency map indicating regions of consistent motion, the motion consistency map having an array of pixels; producing a stereo image pair including a left view image and a right view image by combining the first image and the second image responsive to the motion consistency map; and storing the stereo image pair in a processor-accessible memory.
Abstract:
Objects within two-dimensional video data are modeled by three-dimensional models as a function of object type and motion through manually calibrating a two-dimensional image to the three spatial dimensions of a three-dimensional modeling cube. Calibrated three-dimensional locations of an object in motion in the two-dimensional image field of view of a video data input are determined and used to determine a heading direction of the object as a function of the camera calibration and determined movement between the determined three-dimensional locations. The two-dimensional object image is replaced in the video data input with an object-type three-dimensional polygonal model having a projected bounding box that best matches a bounding box of an image blob, the model oriented in the determined heading direction. The bounding box of the replacing model is then scaled to fit the object image blob bounding box, and rendered with extracted image features.
Abstract:
A method of analyzing a video may include determining at least one of a fastest moving element, a slow moving element and a dominant element within a video based on a first frame of the video and a second frame of the video. The method may also include determining at least one of a foreground and a background within the video based on at least one of the fastest moving element, the slow moving element and the dominant element.
Abstract:
A method of generating a stereoscopic video may include determining movement between a first frame of a monoscopic video and a second frame of the monoscopic video. The method may further include analyzing a camera effect based on the movement. Additionally, the method may include generating a left-eye viewing frame of a stereoscopic video based on the camera effect analysis and generating a right-eye viewing frame of the stereoscopic video based on the camera effect analysis.
Abstract:
A method for converting two-dimensional video to three-dimensional video. The method includes the steps of comparing at least part of video frame x to a corresponding at least part of video frame y to determine movement therebetween, calculating a movement direction and movement extent based on the determined movement, determining viewing frame L and viewing frame R based on the movement direction, and modifying viewing frame R based on the movement direction and the movement extent to create modified viewing frame R′. One alternative embodiment is a video display device for converting two-dimensional video to three-dimensional video. Another alternative embodiment includes one or more device-readable media storing executable instructions that, when executed, configure a video display device to convert two-dimensional video to three-dimensional video.
Abstract:
In one embodiment, a two-dimensional to stereoscopic conversion method, comprising: estimating a local motion region in a first image relative to one or more second images, the first and the one or more second images comprising two-dimensional images; generating a color model based on the local motion region; calculating a similarity value for each of at least one image pixel selected from the first image based on the color model; and assigning a depth value for each of the at least one image pixel selected from the first image based on the calculated similarity value to generate a stereoscopic image, the method performed by one or more processors.
Abstract:
According to some embodiments, systems, methods, apparatus and computer program code for converting 2D video data to 3D video data includes receiving a two dimensional (2D) video feed from a video camera, the feed including a set of image frames, the frames together forming a panorama image, generating a background depth map, extracting for each of the image frames a set of image frame depth maps from the background depth map, generating an updated depth map using the set of image frame depth maps and the background depth map, and rendering an output image, the output image based on the panorama image and the updated depth map, the output image and the panorama image together forming a stereoscopic image pair.