Abstract: Aspects of the disclosure relate generally to allowing users to create their own image navigation experiences. As an example, a set of panoramic images may be identified using manual and/or automated methods. One or more suggested potential paths connecting ones of the panoramic images may be determined. This information may be displayed to a user with an interface that allows the user to create and change relationships between the panoramic images. For example, users may activate the suggested paths and create connections between the panoramic images of the set. Users may also draw their own connecting paths between panoramic images. The panoramic images and the connections between them may be used to provide a navigation experience.

Abstract: Aspects of the disclosure relate generally to allowing users to create their own image navigation experiences. As an example, a set of panoramic images may be identified using manual and/or automated methods. One or more suggested potential paths connecting ones of the panoramic images may be determined. This information may be displayed to a user with an interface that allows the user to create and change relationships between the panoramic images. For example, users may activate the suggested paths and create connections between the panoramic images of the set. Users may also draw their own connecting paths between panoramic images. The panoramic images and the connections between them may be used to provide a navigation experience.

Abstract: Briefly described, one embodiment determines pose of an object of interest at a run time by capturing a first image of a first structured light pattern projected onto a first local surface of the object of interest; determining a first run-time data set from the captured first image, wherein the first run-time data set corresponds to information determined from the first structured light pattern projected onto the first local surface; comparing the determined first run-time data set and a corresponding first reference data set, the first reference data set corresponding to an ideal pose of the first local surface on an ideally posed reference object; and determining at least one first degree of constraint that defines a first partial pose of the first local surface, the at least one first degree of constraint based upon the comparison of the first run-time data set with the corresponding first reference data set.

Abstract: A system and method for identifying objects using a machine-vision based system are disclosed. Briefly described, one embodiment is a method that captures a first image of at least one object with an image capture device, processes the first captured image to find an object region based on a reference two-dimensional model and determines a three-dimensional pose estimation based on a reference three-dimensional model that corresponds to the reference two-dimensional model and a runtime three-dimensional representation of the object region where a point-to-point relationship between the reference three-dimensional models of the object and the runtime three-dimensional representation of the object region is not necessarily previously known. Thus, two-dimensional information or data is used to segment an image and three-dimensional information or data used to perform three-dimensional pose estimation on a segment of the image.

Abstract: A system and method for identifying objects using a machine-vision based system are disclosed. Briefly described, one embodiment is a method that captures a first image of at least one object with an image capture device, processes the first captured image to find an object region based on a reference two-dimensional model and determines a three-dimensional pose estimation based on a reference three-dimensional model that corresponds to the reference two-dimensional model and a runtime three-dimensional representation of the object region where a point-to-point relationship between the reference three-dimensional models of the object and the runtime three-dimensional representation of the object region is not necessarily previously known. Thus, two-dimensional information or data is used to segment an image and three-dimensional information or data used to perform three-dimensional pose estimation on a segment of the image.