Abstract: An exemplary depth capture system emits a first structured light pattern onto a surface of an object included in a real-world scene using a first structured light emitter included within the depth capture system. The depth capture system also emits, concurrently with the emitting of the first structured light pattern, a second structured light pattern onto the surface of the object using a second structured light emitter included within the depth capture system. The emitting of the second structured light pattern is different than the emitting of the first structured light pattern. The depth capture system detects the first and second structured light patterns using one or more optical sensors included within the depth capture system. Based on the detection of the structured light patterns, the depth capture system generates depth data representative of the surface of the object included in the real-world scene.

Abstract: An exemplary depth data generation system accesses first and second depth maps of a real-world scene, the depth maps independently captured using first and second depth map capture techniques, respectively. The first and second depth maps include, respectively, first and second depth data points both representative of a same physical point on a surface of an object in the real-world scene. Based on the first and second depth map capture techniques and based on an attribute of the surface of the object, the system assigns a first confidence value to the first depth data point and a second confidence value to the second depth data point. Based on the first and second confidence values, the system converges the first and second depth maps to form a converged depth map of the real-world scene that includes a third depth data point representing the physical point on the surface of the object.

Abstract: An exemplary depth data generation system accesses first and second depth maps of a real-world scene, the depth maps independently captured using first and second depth map capture techniques, respectively. The first and second depth maps include, respectively, first and second depth data points both representative of a same physical point on a surface of an object in the real-world scene. Based on the first and second depth map capture techniques and based on an attribute of the surface of the object, the system assigns a first confidence value to the first depth data point and a second confidence value to the second depth data point. Based on the first and second confidence values, the system converges the first and second depth maps to form a converged depth map of the real-world scene that includes a third depth data point representing the physical point on the surface of the object.

Abstract: An exemplary depth data generation system (“system”) accesses a first depth map and a second depth map of surfaces of objects included in a real-world scene. The first and second depth maps are captured independently from one another. The system converges the first and second depth maps into a converged depth map of the surfaces of the objects included in the real-world scene. More specifically, the converging comprises assigning a first confidence value to a first depth data point in the first depth map, assigning a second confidence value to a second depth data point in the second depth map, and generating a third depth data point representing a same particular physical point as the first and second depth data points based on the first and second confidence values and on at least one of the first depth data point and the second depth data point.

Abstract: An exemplary depth capture system emits a first structured light pattern onto a surface of an object included in a real-world scene using a first structured light emitter included within the depth capture system. The depth capture system also emits, concurrently with the emitting of the first structured light pattern, a second structured light pattern onto the surface of the object using a second structured light emitter included within the depth capture system. The emitting of the second structured light pattern is different than the emitting of the first structured light pattern. The depth capture system detects the first and second structured light patterns using one or more optical sensors included within the depth capture system. Based on the detection of the structured light patterns, the depth capture system generates depth data representative of the surface of the object included in the real-world scene.

Abstract: An exemplary depth capture system (“system”) emits, from a first fixed position with respect to a real-world scene and within a first frequency band, a first structured light pattern onto surfaces of objects included in a real-world scene. The system also emits, from a second fixed position with respect to the real-world scene and within a second frequency band, a second structured light pattern onto the surfaces of the objects. The system detects the first and second structured light patterns using one or more optical sensors by way of first and second optical filters, respectively. The first and second optical filters are each configured to only pass one of the structured light patterns and to block the other. Based on the detection of the structured light patterns, the system generates depth data representative of the surfaces of the objects included in the real-world scene.

Abstract: An exemplary depth data generation system (“system”) accesses a first depth map and a second depth map of surfaces of objects included in a real-world scene. The first and second depth maps are captured independently from one another. The system converges the first and second depth maps into a converged depth map of the surfaces of the objects included in the real-world scene. More specifically, the converging comprises assigning a first confidence value to a first depth data point in the first depth map, assigning a second confidence value to a second depth data point in the second depth map, and generating a third depth data point representing a same particular physical point as the first and second depth data points based on the first and second confidence values and on at least one of the first depth data point and the second depth data point.

Abstract: An exemplary depth capture system (“system”) emits, from a first fixed position with respect to a real-world scene and within a first frequency band, a first structured light pattern onto surfaces of objects included in a real-world scene. The system also emits, from a second fixed position with respect to the real-world scene and within a second frequency band, a second structured light pattern onto the surfaces of the objects. The system detects the first and second structured light patterns using one or more optical sensors by way of first and second optical filters, respectively. The first and second optical filters are each configured to only pass one of the structured light patterns and to block the other. Based on the detection of the structured light patterns, the system generates depth data representative of the surfaces of the objects included in the real-world scene.

Abstract: A medical imaging apparatus, processing device or specialized circuit can include an input interface to input scan data of a medical image scan of a target object, a processor to generate an output image from the input scan data, and an output interface to output the output image to, e.g., a display. The processor can execute a first reconstruction of the scan data to obtain an intermediate image of the target object, a high-density forward projection of the intermediate object to obtain generated data, a sinogram updating using both of the generated data and the scan data to obtain a high-resolution sinogram, and a second reconstruction based on the high-resolution sinogram to obtain an output image.

Abstract: A medical imaging apparatus, processing device or specialized circuit can include an input interface to input scan data of a medical image scan of a target object, a processor to generate an output image from the input scan data, and an output interface to output the output image to, e.g., a display. The processor can execute a first reconstruction of the scan data to obtain an intermediate image of the target object, a high-density forward projection of the intermediate object to obtain generated data, a sinogram updating using both of the generated data and the scan data to obtain a high-resolution sinogram, and a second reconstruction based on the high-resolution sinogram to obtain an output image.