Abstract: A sensor device for generating a depth map of an object includes a projector unit, a receiver unit, and a control unit. The projector unit projects multiple illumination patterns in a predefined projection solid angle, determining for each solid angle whether to project light. The receiver unit, equipped with multiple pixels, detects reflected light intensities during illumination and generates events when intensity changes exceed a threshold. The control unit adjusts illumination patterns, collects event data, and maps the reflected patterns to corresponding pixels. This enables the generation of a depth map by associating solid angles with pixel locations based on event data.

Abstract: A method and system for rendering an augmented reality scene on a mobile computing device tracks a real-world scene and/or a viewpoint of a user with one or more event-based vision sensors and blends an augmented reality scene displayed on the mobile computing device based on the viewpoint of the user and a scene map of the real-world scene and on the tracking of the one or more event-based vision sensors. Event-based vision sensors offer many advantages, mainly by intrinsically compressing the data stream and thus reducing the amount of data that a processing unit needs to perform. Furthermore, the event-based vision sensor pixels continuously sense the visual changes in the scene and report them with a very low latency. This makes the event-based vision sensor an ideal sensor for always-on tasks such as visual tracking and smart sensor control or data enhancement of secondary sensing modalities.

Abstract: A method and system for rendering an augmented reality scene on a mobile computing device tracks a real-world scene and/or a viewpoint of a user with one or more event-based vision sensors and blends an augmented reality scene displayed on the mobile computing device based on the viewpoint of the user and a scene map of the real-world scene and on the tracking of the one or more event-based vision sensors. Event-based vision sensors offer many advantages, mainly by intrinsically compressing the data stream and thus reducing the amount of data that a processing unit needs to perform. Furthermore, the event-based vision sensor pixels continuously sense the visual changes in the scene and report them with a very low latency. This makes the event-based vision sensor an ideal sensor for always-on tasks such as visual tracking and smart sensor control or data enhancement of secondary sensing modalities.

Abstract: A method and system for rendering an augmented reality scene on a mobile computing device tracks a real-world scene and/or a viewpoint of a user with one or more event-based vision sensors and blends an augmented reality scene displayed on the mobile computing device based on the viewpoint of the user and a scene map of the real-world scene and on the tracking of the one or more event-based vision sensors. Event-based vision sensors offer many advantages, mainly by intrinsically compressing the data stream and thus reducing the amount of data that a processing unit needs to perform. Furthermore, the event-based vision sensor pixels continuously sense the visual changes in the scene and report them with a very low latency. This makes the event-based vision sensor an ideal sensor for always-on tasks such as visual tracking and smart sensor control or data enhancement of secondary sensing modalities.

Abstract: A method and system for rendering an augmented reality scene on a mobile computing device tracks a real-world scene and/or a viewpoint of a user with one or more event-based vision sensors and blends an augmented reality scene displayed on the mobile computing device based on the viewpoint of the user and a scene map of the real-world scene and on the tracking of the one or more event-based vision sensors. Event-based vision sensors offer many advantages, mainly by intrinsically compressing the data stream and thus reducing the amount of data that a processing unit needs to perform. Furthermore, the event-based vision sensor pixels continuously sense the visual changes in the scene and report them with a very low latency. This makes the event-based vision sensor an ideal sensor for always-on tasks such as visual tracking and smart sensor control or data enhancement of secondary sensing modalities.

Abstract: A method of using an in-situ aerial image sensor array is disclosed to separate and remove the focal plane variations caused by the image sensor array non-flatness and/or by the exposure tool by collecting sensor image data at various nominal focal planes and by determining best focus at each sampling location by analysis of the through-focus data. In various embodiments, the method provides accurate image data at best focus anywhere in the exposure field, image data covering an exposure-dose based process window area, and a map of effective focal plane distortions. The focus map can be separated into contributions from the exposure tool and contributions due to topography of the image sensor array by suitable calibration or self-calibration procedures. The basic method enables a wide range of applications, including for example qualification testing, process monitoring, and process control by deriving optimum process corrections from analysis of the image sensor data.

Abstract: One embodiment of a method for detecting, sampling, analyzing, and correcting hot spots in an integrated circuit design allows the identification of the weakest patterns within each design layer, the accurate determination of the impact of process drifts upon the patterning performance of the real mask in a real scanner, and the optimum process correction, process monitoring, and RET improvements to optimize integrated circuit device performance and yield. The combination of high speed simulation coupled with massive data collection capability on actual aerial images and/or resist images at the specific patterns of interest provides a complete methodology for optimum RET implementation and process monitoring.

Abstract: There are many inventions described and illustrated herein. In one aspect, the present invention is directed to a technique of, and system for autonomously monitoring fabrication equipment, for example, integrated circuit fabrication equipment. In one embodiment of this aspect of the invention, the present invention is an autonomous monitoring device including one or more event sensors (for example, acceleration, motion, velocity and/or inertial sensing device(s)) to detect a predetermined event of or by the fabrication equipment (for example, an event that is indicative of the onset, commencement, initiation and/or launch of fabrication process or sub-processes of or by the fabrication equipment). In response thereto, one or more process parameter sensors sample, sense, detect, characterize, analyze and/or inspect one or more parameters of the process in real time (i.e., during the fabrication process).