Intellectual Discovery Co., Ltd.

Conversion Works, Inc.

Christopher Levi Simmons

David Alan Spooner

Danny D Lowe

Steven Birtwistle

Gregory R Keech

Natascha Wallner

Jonathan Adelman

Sonny Chan

The present invention is directed to systems and methods for controlling 2-D to 3-D image conversion. The system and method includes receiving an image and masking the objects in the image using segmentation layers Each segmentation layer can have weighted values for static and dynamic features. Iterations are used to form the final image which, if desired, can be formed using less than all of the segmentation layers. A final iteration can be run with the weighted values equal for static and dynamic features.

Systems and methods 2-D to 3-D conversion using depth access segiments to define an object

The present invention is directed to systems and methods for controlling 2-D to 3-D image conversion and/or generation. The methods and systems use auto-fitting techniques to create a mask based upon tracking features from frame to frame. When features are determined to be missing they are added prior to auto-fitting the mask.

System and method for using feature tracking techniques for the generation of masks in the conversion of two-dimensional images to three-dimensional images

Embodiments use point clouds to form a three dimensional image of an object. The point cloud of the object may be formed from analysis of two dimensional images of the object. Various techniques may be used on the point cloud to form a three dimensional model of the object which is then used to create a stereoscopic representation of the object.

System and method for processing video images

The present invention is directed to systems and methods for controlling 2-D to 3-D image conversion. In one embodiment, a mask is generated from an object model of the image. The mask is then used to from a 2-D mesh which is then converted to a 3-D volume mesh. The 3-D volume mesh is then used to produce 3-D image conversion.

Systems and methods for 2-D to 3-D image conversion using mask to model, or model to mask, conversion

The present invention is directed to a system and method for interactive and iterative reconstruction in a manner that helps to reduce computational requirements by generating a model from a subset of the available data, and then refining that model using additional data. Example embodiments directed to scene reconstruction, reconstruct a 3D scene from a plurality of 2D images of that scene by first generating a model of the 3D scene from a subset a of the 2D images. The model can then be refined using specific characteristics of each image in the subset that are calculated using the other images in the subset. The model is further refined using images not in the original subset.

Methodology for 3D scene reconstruction from 2D image sequences

The present invention is directed to systems and methods for processing 2-D to 3-D image conversion. The system and method includes erode filling when an object has been removed from an image. In one embodiment, a target binary t image mask of the removed object is used for comparison with a binary source mask of the image. In an iterative process, color differences between pixels in the target mask and pixels in the source mask are identified and the pixels in the target mask are changed working from the periphery of the target mask to the center of the mask. Color noise is eliminated in the filled region of the target mask and, if desired, random color noise is added to the filled target mask.

Systems and methods for filling occluded information for 2-D to 3-D conversion

Embodiments use point clouds to form a three dimensional image of an object. The point cloud of the object may be formed from analysis of two dimensional images of the object. Various techniques may be used on the point cloud to form a 3D model of the object which is then used to create a stereoscopic representation of the object.

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Calgary, Canada

Christopher Levi Simmons