Abstract: An event-based vision sensor system comprises an event-based pixel array including pixels that detect light, a readout circuit for reading out events associated with light received by each pixel and with the position it occupies in the array, and a memory controller that enables writing of each event, or event-related data, associated with a certain pixel to a certain address in a memory.

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 dynamic vision sensor such as an event based vision sensor employs analog to digital converters (ADC), such as ramp ADCs, that analog to digital converts the signals from photoreceptors. Only previous light values need to be stored in the pixels. This is accomplished by generating three ramps. In addition, log compression can be implemented by increasing the count linearly while increasing the reference voltage exponentially, or increasing the count logarithmically while increasing the reference voltage linearly.

Abstract: A dynamic vision sensor such as an event based vision sensor employs analog to digital converters (ADC), such as ramp ADCs, that analog to digital converts the signals from photoreceptors. Current and previous light values are then stored and compared digitally. In addition, log compression can be implemented by increasing the count linearly while increasing the reference voltage exponentially, or increasing the count logarithmically while increasing the reference voltage linearly.

Abstract: A dynamic vision sensor (DVS) or change detection sensor reacts to changes in light intensity and in this way monitors how a scene changes. This disclosure covers both single pixel and array architectures. The DVS may contain one pixel or 2-dimensional or 1-dimensional array of pixels. The change of intensities registered by pixels are compared, and pixel addresses where the change is positive or negative are recorded and processed. Analyzing frames based on just three values for pixels, increase, decrease or unchanged, the proposed DVS can process visual information much faster than traditional computer vision systems, which correlate multi-bit color or gray level pixel values between successive frames.

Abstract: A dynamic vision sensor (DVS) or change detection sensor reacts to changes in light intensity and in this way monitors how a scene changes. This disclosure covers both single pixel and array architectures. The DVS may contain one pixel or 2-dimensional or 1-dimensional array of pixels. The change of intensities registered by pixels are compared, and pixel addresses where the change is positive or negative are recorded and processed. Analyzing frames based on just three values for pixels, increase, decrease or unchanged, the proposed DVS can process visual information much faster than traditional computer vision systems, which correlate multi-bit color or gray level pixel values between successive frames.

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: An event-based vision sensor is fabricated using an advanced stacking technique, known as Three-Dimensional Integrated Circuit, which stacks more wafers (or dies) and interconnects them vertically. The electronic integrated circuits of the sensor are then distributed between the two or more electrically connected dies.

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: In dynamic vision sensor (DVS) or change detection sensors, the chip or sensor is configured to control or modulate the event rate. For example, this control can be used to keep the event rate close to a desired rate or within desired bounds. Adapting the configuration of the sensor to the scene by changing the ON-event and/or the OFF-event thresholds, allows having necessary amount of data, but not much more than necessary, such that the overall system gets as much information about its state as possible.

Abstract: In dynamic vision sensor (DVS) or change detection sensors, the chip or sensor is configured to control or modulate the event rate. For example, this control can be used to keep the event rate close to a desired rate or within desired bounds. Adapting the configuration of the sensor to the scene by changing the ON-event and/or the OFF-event thresholds, allows having necessary amount of data, but not much more than necessary, such that the overall system gets as much information about its state as possible.

Abstract: A dynamic vision sensor such as an event based vision sensor employs analog to digital converters (ADC), such as ramp ADCs, that analog to digital converts the signals from photoreceptors. Current and previous light values are then stored and compared digitally. In addition, log compression can be implemented by increasing the count linearly while increasing the reference voltage exponentially, or increasing the count logarithmically while increasing the reference voltage linearly.

Abstract: A dynamic vision sensor such as an event based vision sensor employs analog to digital converters (ADC), such as ramp ADCs, that analog to digital converts the signals from photoreceptors. Only previous light values need to be stored in the pixels. This is accomplished by generating three ramps. In addition, log compression can be implemented by increasing the count linearly while increasing the reference voltage exponentially, or increasing the count logarithmically while increasing the reference voltage linearly.

Abstract: In an image sensor, some pixels in an array contain a sampling circuit to sample the light intensity and a capacitor to store an analog value representing the intensity at that pixel. Alternatively, a group of pixel circuits will be equipped with such sampling and capacitor circuits. This allows simple redundancy-reducing computations with a relatively simple pixel architecture.

Abstract: An event-based vision sensor system comprises an event-based pixel array including pixels that detect light, a readout circuit for reading out events associated with light received by each pixel and with the position it occupies in the array, and a memory controller that enables writing of each event, or event-related data, associated with a certain pixel to a certain address in a memory.

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 comprising one or more event-based vision sensors for monitoring an environment and one or more depth sensors monitoring the environment as well as potentially additional sensors to monitor the environment such as inertial measurement units and image sensors. The device as a processor assembly will then monitor the event-based vision sensor and the depth sensor and other sensors and determine whether to adapt a control schem, such as activate, the depth sensor to acquire depth information of the environment based on the response of the event-based vision sensor. This approach leverages advantages of event-based sensors to reduce the power consumption but still react quickly to such changes by continuously measuring intervals directly relating to the minimally admitted delays in the application for which depth measurements or inferred data are used.

Abstract: An event-based vision sensor system comprises an event-based pixel array including pixels that detect light, a readout circuit for reading out events associated with light received by each pixel and with the position it occupies in the array, and a memory controller that enables writing of each event, or event-related data, associated with a certain pixel to a certain address in a memory.

Abstract: A dynamic vision sensor (DVS) or change detection sensor reacts to changes in light intensity and in this way monitors how a scene changes. This disclosure covers both single pixel and array architectures. The DVS may contain one pixel or 2-dimensional or 1-dimensional array of pixels. The change of intensities registered by pixels are compared, and pixel addresses where the change is positive or negative are recorded and processed. Analyzing frames based on just three values for pixels, increase, decrease or unchanged, the proposed DVS can process visual information much faster than traditional computer vision systems, which correlate multi-bit color or gray level pixel values between successive frames.

Abstract: A dynamic vision sensor (DVS) or change detection sensor reacts to changes in light intensity and in this way monitors how a scene changes. This disclosure covers both single pixel and array architectures. The DVS may contain one pixel or 2-dimensional or 1-dimensional array of pixels. The change of intensities registered by pixels are compared, and pixel addresses where the change is positive or negative are recorded and processed. Analyzing frames based on just three values for pixels, increase, decrease or unchanged, the proposed DVS can process visual information much faster than traditional computer vision systems, which correlate multi-bit color or gray level pixel values between successive frames.