Disclosed is a robot cleaner including a light source for irradiating light, a sensor for sensing that the light irradiated from the light source is reflected, and a controller that processes an image using the light sensed by the sensor to calculate a distance value of an individual location of the corresponding image, wherein it is determined that there is an obstacle when there is a dead zone in the image processed by the controller.

Disclosed is a robot cleaner including a light source for irradiating light, a sensor for sensing that the light irradiated from the light source is reflected, and a controller that processes an image using the light sensed by the sensor to calculate a distance value of an individual location of the corresponding image, wherein it is determined that there is an obstacle when there is a dead zone in the image processed by the controller.

A detection device includes: a detector that detects an object from a first viewpoint; an information calculator that calculates first model information including shape information on the object from the first viewpoint by using detection results of the detector; a light source calculator that calculates light source information on the light source by using a first taken image obtained by imaging a space including a light source that irradiates the object with illumination light and including the object; and a position calculator that calculates a positional relation between the first viewpoint and the object by using the light source information as information used to integrate the first model information and second model information including shape information obtained by detecting the object from a second viewpoint different from the first viewpoint.

A detection device includes: a detector that detects an object from a first viewpoint; an information calculator that calculates first model information including shape information on the object from the first viewpoint by using detection results of the detector; a light source calculator that calculates light source information on the light source by using a first taken image obtained by imaging a space including a light source that irradiates the object with illumination light and including the object; and a position calculator that calculates a positional relation between the first viewpoint and the object by using the light source information as information used to integrate the first model information and second model information including shape information obtained by detecting the object from a second viewpoint different from the first viewpoint.

A system and method for gaging the shape of a curved panel includes, as components, (1) a system and method for acquiring three-dimensional surface data corresponding to the panel, and (2) a system and method for receiving the acquired surface data, comparing the acquired surface to a pre-defined surface description, and developing indicia of the level of conformance of the contoured panel to the pre-defined specification. The surface data acquisition system includes a conveyor for conveying the panel, at least one display projecting a preselected contrasting pattern, and at least one camera. The camera(s) and display(s) are uniquely paired and are mounted in a spaced-apart relationship a known distance and angle from the surface of the panel such that the camera detects the reflected image of the pattern projected on the surface of the panel from its associated display.

A system and method for gaging the shape of a curved panel includes, as components, (1) a system and method for acquiring three-dimensional surface data corresponding to the panel, and (2) a system and method for receiving the acquired surface data, comparing the acquired surface to a pre-defined surface description, and developing indicia of the level of conformance of the contoured panel to the pre-defined specification. The surface data acquisition system includes a conveyor for conveying the panel, at least one display projecting a preselected contrasting pattern, and at least one camera. The camera(s) and display(s) are uniquely paired and are mounted in a spaced-apart relationship a known distance and angle from the surface of the panel such that the camera detects the reflected image of the pattern projected on the surface of the panel from its associated display.

Shape measurement of a specular object even in the presence of multiple intra-object reflections such as those at concave regions of the object. Silhouettes of the object are extracted, by positioning the object between a camera and a background. A visual hull of the object is reconstructed based on the extracted silhouettes, such as by image capture of shadows of the object projected onto a screen, and image capture of reflections by the surface of the object of coded patterns onto the screen. The visual hull is used to distinguish between direct (single) reflections of the coded patterns at the surface of the object and multiple reflections. Only the direct (single) reflections are used to triangulate camera rays and light rays onto the surface of the object, with multiple reflections being excluded. The 3D surface shape may be derived by voxel carving of the visual hull, in which voxels along the light path of direct reflections are eliminated. For surface reconstruction of heterogeneous objects, which exhibit both diffuse and specular reflectivity, variations in the polarization state of polarized light may be used to separate between a diffuse component of reflection and a specular component.

Enhanced methods and systems for generating both a geometry model and an optical-reflectance model (an object reconstruction model) for a physical object, based on a sparse set of images of the object under a sparse set of viewpoints. The geometry model is a mesh model that includes a set of vertices representing the object's surface. The reflectance model is SVBRDF that is parameterized via multiple channels (e.g., diffuse albedo, surface-roughness, specular albedo, and surface-normals). For each vertex of the geometry model, the reflectance model includes a value for each of the multiple channels. The object reconstruction model is employed to render graphical representations of a virtualized object (a VO based on the physical object) within a computation-based (e.g., a virtual or immersive) environment. Via the reconstruction model, the VO may be rendered from arbitrary viewpoints and under arbitrary lighting conditions.

Enhanced methods and systems for generating both a geometry model and an optical-reflectance model (an object reconstruction model) for a physical object, based on a sparse set of images of the object under a sparse set of viewpoints. The geometry model is a mesh model that includes a set of vertices representing the object's surface. The reflectance model is SVBRDF that is parameterized via multiple channels (e.g., diffuse albedo, surface-roughness, specular albedo, and surface-normals). For each vertex of the geometry model, the reflectance model includes a value for each of the multiple channels. The object reconstruction model is employed to render graphical representations of a virtualized object (a VO based on the physical object) within a computation-based (e.g., a virtual or immersive) environment. Via the reconstruction model, the VO may be rendered from arbitrary viewpoints and under arbitrary lighting conditions.

An apparatus to generate data relating to a specular surface of an object, the apparatus including a screen that is movable relative to the object, a graphic rendered on the screen' wherein the graphic is notionally divided into contiguous segments such that the graphic content in each segment allows that segment to be distinguished from a plurality of other segments, at least one camera for capturing successive frames of the object' illuminated by said graphic, during said relative movement of the screen, and a computing device that accepts data from pixels of the captured frames.