Abstract: Disclosed is an image adjustment apparatus including a receiver which is configured to receive a first input image of an object which is time-synchronously captured and a second input image in which a motion event of the object is sensed time-asynchronously, and an adjuster which is configured to adjust the first input image and the second input image.

Abstract: An event signal processing method and an event-based sensor performing the event signal processing method are provided. The event signal processing method includes receiving an activation signal to indicate sensing of an event from a sensor array, increasing the cumulative event number of a sensing area corresponding to the activation signal among sensing areas of the sensor array, reducing the cumulative event number of each of the sensing areas based on a parameter; and determining, as a flickering area, a sensing area among the sensing areas, of which the cumulative event number exceeds a threshold.

Abstract: Disclosed is an image adjustment apparatus including a receiver which is configured to receive a first input image of an object which is time-synchronously captured and a second input image in which a motion event of the object is sensed time-asynchronously, and an adjuster which is configured to adjust the first input image and the second input image.

Abstract: An object detection method and a neural network system for object detection are disclosed. The object detection method acquires a current frame of a sequence of frames representing an image sequence, and extracts a feature map of the current frame. The extracted feature map is pooled with information of a pooled feature map of a previous frame to thereby obtain a pooled feature map of the current frame. An object is detected from the pooled feature map of the current frame. A dynamic vision sensor (DVS) may be utilized to provide the sequence of frames. Improved object detection accuracy may be realized, particularly when object movement speed is slow.

Abstract: An object recognition apparatus and an object recognition method are provided. The object recognition method includes generating an input image based on an event flow of an object, generating a composite feature based on features extracted by a plurality of recognizers, and recognizing the object based on the composite feature.

Abstract: Methods and apparatuses for time alignment calibration are provided including acquiring an event-stream and video images of a target object which are simultaneously shot by a dynamic vision sensor and an assistant vision sensor, determining a key frame that reflects obvious movement of the target object from the video images, mapping effective pixel positions of the target object in the key frame and effective pixel positions of the target object in the neighboring frames according to a spatial relative relation between the dynamic vision sensor and the assistant vision sensor, determining a first target object template that covers events in a first event-stream segment from the plurality of target object templates, and using a time alignment relation of an intermediate instant of the first event-stream segment and a timestamp of a frame corresponding to the first target object template between the dynamic vision sensor and the assistant vision sensor.

Abstract: An image generating method and an image generating apparatus are provided. The image generating method includes generating a first image based on first event signals that are output from an event-based vision sensor during a first time period and stored in a buffer, generating a second image based on second event signals that are output from the event-based vision sensor during a second time period and stored in the buffer, and aligning the first image and the second image to generate a third image having a quality that is higher than qualities of the first image and the second image.

Abstract: An event signal processing method and apparatus are provided. The event signal processing method includes receiving, from an event-based sensor, event signals including timestamps, generating a first timestamp map based on the timestamps, and interpolating a new timestamp into the first timestamp map based on at least two timestamps of the first timestamp map, to generate a second timestamp map.

Abstract: An image processing device includes a vision sensor and a processor. The vision sensor generates a plurality of events in which an intensity of light changes and generates a plurality of timestamps depending on times when the events occur. In addition, the processor may regenerate a timestamp of a pixel where an abnormal event occurs, based on temporal correlation of the events.

Abstract: An event detecting device may include an event signal generator configured to output a plurality of event signals, each including a first data and a second data having mutually complementary attributes and respective address data indicating positions of pixels having output the first data and the second data, a data manager configured to store one of the first data and the second data of a first one of the plurality of event signals and the respective address data in a buffer as first sub data when only one of the first data and the second data of the first one of the plurality of event signals includes the event information, and an output signal generator configured to generate an output signal using the first sub data and a second sub data when the second sub data, different from the first sub data, is stored in the buffer.

Abstract: A pixel includes a photoelectric device, a current readout unit configured to detect an electric current flowing in the photoelectric device to generate an input voltage, an event determination unit configured to determine an event occurrence and an event type responsive to the input voltage, and configured to output an event detection signal, and an event output unit configured to store the event detection signal for an event-storage period and configured to output the stored event detection signal responsive to an expiration of the event-storage period.

Abstract: A method of displaying a menu based on at least one of a depth information and a space gesture is provided. The method including determining depth information corresponding to a distance from a screen of a user terminal to a hand of a user; identifying at least one layer among a plurality of layers based on the depth information; and applying a graphic effect to the identified layer so that a menu page corresponding to the at least one identified layer is displayed on the screen of the user terminal.

Abstract: An image deblurring method and an image deblurring apparatus are provided. The image deblurring method includes acquiring a blurred image and a dynamic vision sensor (DVS) event set that is recorded by a DVS while the blurred image is exposed, and deblurring the blurred image, based on the DVS event set.

Abstract: A user input processing method is provided. The user input processing method determines, based on a recognition reliability of a user input for a function, a delay time and whether the function is to be performed, the function being determined in advance, and controls the function based on the delay time and whether the function is to be performed.

Abstract: A method and apparatus for detecting an object using an event-based sensor is provided. An object detection method includes determining a feature vector based on target pixels and neighbor pixels included in an event image, and determining a target object corresponding to the target pixels based on the feature vector.

Abstract: A method and apparatus for processing data are provided. The processor includes an input buffer, a data extractor, a multiplier, and an adder. The input buffer receives data and stores the data. The data extractor extracts kernel data corresponding to a kernel in the data from the input buffer. The multiplier multiplies the extracted kernel data by a convolution coefficient. The adder calculates a sum of multiplication results from the multiplier.

Abstract: A method of displaying a menu based on at least one of a depth information and a space gesture is provided. The method including determining depth information corresponding to a distance from a screen of a user terminal to a hand of a user; identifying at least one layer among a plurality of layers based on the depth information; and applying a graphic effect to the identified layer so that a menu page corresponding to the at least one identified layer is displayed on the screen of the user terminal.

Abstract: A method and an apparatus for displaying a screen in response to an event related to a motion of an external object, are provided. The method includes generating an event signal in response a motion of an external object being sensed, sensing a movement of the external object relative to an apparatus based on the event signal, and displaying a screen based on the movement of the external object.

Abstract: Apparatuses and methods for sensing spatial information based on a vision sensor are disclosed. The apparatus and method recognize the spatial information of an object sensed by the vision sensor that senses a temporal change of light. The light being input into the vision sensor is artificially changed using a change unit configured to change the light being input to the vision sensor.

Abstract: Exemplary embodiments provide an image vision processing method, device and equipment and relate to: determining parallax and depth information of event pixel points in a dual-camera frame image acquired by Dynamic Vision Sensors; determining multiple neighboring event pixel points of each non-event pixel point in the dual-camera frame image; determining, according to location information of each neighboring event pixel point of each non-event pixel point, depth information of the non-event pixel point; and performing processing according to the depth information of each pixel point in the dual-camera frame image. Since non-event pixel points are not required to participate in the matching of pixel points, even if it is difficult to distinguish between the non-event pixel points or the non-event pixel points are occluded, depth information of the non-event pixel points can be accurately determined according to the location information of neighboring event pixel points.