Abstract:
A combination of three computational components may provide memory and computational efficiency while producing results with little latency, e.g., output can begin with the second frame of video being processed. Memory usage may be reduced by maintaining key frames of video and pose information for each frame of video. Additionally, only one global volumetric structure may be maintained for the frames of video being processed. To be computationally efficient, only depth information may be computed from each frame. Through fusion of multiple depth maps from different frames into a single volumetric structure, errors may average out over several frames, leading to a final output with high quality.
Abstract:
A combination of three computational components may provide memory and computational efficiency while producing results with little latency, e.g., output can begin with the second frame of video being processed. Memory usage may be reduced by maintaining key frames of video and pose information for each frame of video. Additionally, only one global volumetric structure may be maintained for the frames of video being processed. To be computationally efficient, only depth information may be computed from each frame. Through fusion of multiple depth maps from different frames into a single volumetric structure, errors may average out over several frames, leading to a final output with high quality.
Abstract:
Global and local light detection techniques in optical sensor systems are described. In one or more implementations, a global lighting value is generated that describes a global lighting level for a plurality of optical sensors based on a plurality of inputs received from the plurality of optical sensors. An illumination map is generated that describes local lighting conditions of respective ones of the plurality of optical sensors based on the plurality of inputs received from the plurality of optical sensors. Object detection is performed using an image captured using the plurality of optical sensors along with the global lighting value and the illumination map.
Abstract:
A holographic interaction device is described. In one or more implementations, an input device includes an input portion comprising a plurality of controls that are configured to generate signals to be processed as inputs by a computing device that is communicatively coupled to the controls. The input device also includes a holographic recording mechanism disposed over a surface of the input portion, the holographic recording mechanism is configured to output a hologram in response to receipt of light, from a light source, that is viewable by a user over the input portion.
Abstract:
A 3D silhouette sensing system is described which comprises a stereo camera and a light source. In an embodiment, a 3D sensing module triggers the capture of pairs of images by the stereo camera at the same time that the light source illuminates the scene. A series of pairs of images may be captured at a predefined frame rate. Each pair of images is then analyzed to track both a retroreflector in the scene, which can be moved relative to the stereo camera, and an object which is between the retroreflector and the stereo camera and therefore partially occludes the retroreflector. In processing the image pairs, silhouettes are extracted for each of the retroreflector and the object and these are used to generate a 3D contour for each of the retroreflector and object.
Abstract:
A display that renders realistic objects allows a designer to redesign a living space in real time based on an existing layout. A computer system renders simulated objects on the display such that the simulated objects appear to the viewer to be in substantially the same place as actual objects in the scene. The displayed simulated objects can be spatially manipulated on the display through various user gestures. A designer can visually simulate a redesign of the space in many ways, for example, by adding selected objects, or by removing or rearranging existing objects, or by changing properties of those objects. Such objects also can be associated with shopping resources to enable related goods and services to be purchased, or other commercial transactions to be engaged in.
Abstract:
Object detection techniques for use in conjunction with optical sensors is described. In one or more implementations, a plurality of inputs are received, each of the inputs being received from a respective one of a plurality of optical sensors. Each of the plurality of inputs are classified using machine learning as to whether the inputs are indicative of detection of an object by a respective said optical sensor.