Abstract: A system for recognizing objects under different environmental conditions by manipulating an original image with light and animation effects in real time and comparing the result with an input frame. This improves the ability of the system to detect and recognize a matching real world object in a variety of conditions. 3D rendering techniques are used to create a new and more accurate reference model as compared to current static object descriptions. The system is implemented on a computer with GPU capabilities. The real world object to be recognized is configured in the system as a 3D object, and is manipulated to create custom environmental conditions that can be adjusted by the user to optimize detection and recognition in an environment appropriate for each user.

Abstract: The present system provides a tool to estimate the relative pose of a generic object with respect to a camera view-point by processing 2D images from a monocular camera in real-time. The capability of solving the pose estimation problem relies on the robust detection and matching in consecutive image frames of significant visual features belonging to an object of interest. To accomplish this, the system incorporates 3D modeling of the object of interest. In one embodiment, the shape of interest may be approximated by a parametric surface such as a cylinder, sphere, ellipsoid, or even complex non-parametric models. The system can restrain information retrieved at a 2D image level to estimate parameters about the pose. In operation, the accuracy of the 3D pose estimation of the object is a function of the degree of approximation of the selected model and the ability to select and track relevant features across consecutive image frames.

Abstract: An image processing for recognition objectives system including uploading n image to a processor and associated memory via a network, dividing the images into a plurality of sub-images, preprocessing, uploading an image to be recognized from an image source to the processor and associated memory, pre-processing the image to be recognized and a first the plurality of sub-images, extracting key features from the image to be recognized and a first of the plurality of sub-images, comparing the key features of the image and the first of the sub-images, if there is a match, display the match and if there is no match, advance to the next of the plurality of sub-images and repeat until a match is determined.

Abstract: Methods and systems are provided for visualizing and rendering three-dimensional spaces using two-dimensional content. To create three-dimensional visualizations, the visualization system retrieves two-dimensional content data from a content source, defines at least one layer within the content data, defines at least one anchor within each layer, and defines at least one element within each layer, wherein each element represents an object at a three-dimensional boundary as viewed from at least one of the anchors. To render three-dimensional visualizations, the visualization system identifies an anchor within a layer for which to generate a scene, defines a three-dimensional boundary to capture at least one element within the scene, defines a texture of the three-dimensional boundary, wherein the texture forms a background for the scene, and renders the scene representing the view at the anchor.

Abstract: An image recognition system in a cloud environment including uploading a plurality of images to the cloud environment, preprocessing the plurality of images, determining image classifiers for each of the plurality of images, extracting the features of each of the plurality of images, storing the images, features and classifiers, determining the image classifiers and key features of an image to be recognized from a multiplatform image device, selecting from the plurality of images, images which have the same classifiers as the image to be identified, matching a best one of the selected images with the image to be identified and displaying the match on a display of the .multi-platform image device. The system further functions by performing one or more of the above in the multiplatform imaging device and/or cloud environment.

Abstract: Methods and systems are provided for visualizing and rendering three-dimensional spaces using two-dimensional content. To create three-dimensional visualizations, the visualization system retrieves two-dimensional content data from a content source, defines at least one layer within the content data, defines at least one anchor within each layer, and defines at least one element within each layer, wherein each element represents an object at a three-dimensional boundary as viewed from at least one of the anchors. To render three-dimensional visualizations, the visualization system identifies an anchor within a layer for which to generate a scene, defines a three-dimensional boundary to capture at least one element within the scene, defines a texture of the three-dimensional boundary, wherein the texture forms a background for the scene, and renders the scene representing the view at the anchor.

Abstract: A system for recognizing objects under different environmental conditions by manipulating an original image with light and animation effects in real time and comparing the result with an input frame. This improves the ability of the system to detect and recognize a matching real world object in a variety of conditions. 3D rendering techniques are used to create a new and more accurate reference model as compared to current static object descriptions. The system is implemented on a computer with GPU capabilities. The real world object to be recognized is configured in the system as a 3D object, and is manipulated to create custom environmental conditions that can be adjusted by the user to optimize detection and recognition in an environment appropriate for each user.

Abstract: Rendering systems and methods are provided herein, which generate, from received two-dimensional (2D) object information related to an object and 3D model representations, a textured model of the object. The textured model is placed in training scenes which are used to generate various picture sets of the modeled object in the training scenes. These picture sets are used to train image recognition and object tracking computer systems.

Abstract: A visual positioning system for indoor locations with associated content is provided herein. The system has a map creator and a viewer. The map creator maps the indoor location by acquiring plans thereof, detects paths through the location and associates with the paths frames relating to objects and views of the paths. The viewer allows a user to orient in the indoor location by locating the user with respect to a path. The viewer enhances GPS/WIFI/3G data by matching user-captured images with the frames, and then interactively displaying the user data from the mapped paths with respect to user queries.

Abstract: The present system provides a tool to estimate the relative pose of a generic object with respect to a camera view-point by processing 2D images from a monocular camera in real-time. The capability of solving the pose estimation problem relies on the robust detection and matching in consecutive image frames of significant visual features belonging to an object of interest. To accomplish this, the system incorporates 3D modeling of the object of interest. In one embodiment, the shape of interest may be approximated by a parametric surface such as a cylinder, sphere, ellipsoid, or even complex non-parametric models. The system can restrain information retrieved at a 2D image level to estimate parameters about the pose. In operation, the accuracy of the 3D pose estimation of the object is a function of the degree of approximation of the selected model and the ability to select and track relevant features across consecutive image frames.

Abstract: An image processing for recognition objectives system including uploading n image to a processor and associated memory via a network, dividing the images into a plurality of sub-images, preprocessing, uploading an image to be recognized from an image source to the processor and associated memory, pre-processing the image to be recognized and a first the plurality of sub-images, extracting key features from the image to be recognized and a first of the plurality of sub-images, comparing the key features of the image and the first of the sub-images, if there is a match, display the match and if there is no match, advance to the next of the plurality of sub-images and repeat until a match is determined.

Abstract: An image recognition system in a cloud environment including uploading a plurality of images to the cloud environment, preprocessing the plurality of images, determining image classifiers for each of the plurality of images, extracting the features of each of the plurality of images, storing the images, features and classifiers, determining the image classifiers and key features of an image to be recognized from a multiplatform image device, selecting from the plurality of images, images which have the same classifiers as the image to be identified, matching a best one of the selected images with the image to be identified and displaying the match on a display of the .multi-platform image device. The system further functions by performing one or more of the above in the multiplatform imaging device and/or cloud environment.