Robotics
Event camera
Definition
An event camera is a vision sensor whose pixels asynchronously report changes in brightness instead of exposing complete image frames at fixed intervals. Each event normally carries a pixel location, timestamp, and change polarity.
Also known as: Event-based camera, Event vision sensor
Updated
Pixels report change rather than frames
A conventional camera samples an array of intensities at a sequence of exposure times. An event camera instead lets each pixel emit an event when the change in its measured log intensity crosses a threshold. The output is an asynchronous stream containing the pixel coordinates, time, and whether brightness increased or decreased, as described in the event-based vision survey.
The stream is sparse when little changes and dense around moving edges or changing illumination. It is not an ordinary video with missing frames, so algorithms usually operate on events directly or accumulate them into a chosen representation.
Why robots use event streams
The sensor's fine timing and lack of a global frame exposure can help when a robot or observed object moves quickly. The cited survey covers applications including feature tracking, optical flow, reconstruction, segmentation, and recognition. Robotics systems can also combine events with an inertial measurement unit for motion estimation.
For a humanoid, possible uses include tracking during rapid head motion, observing a fast hand-object interaction, or maintaining visual estimates across strong changes in illumination. Those benefits depend on the sensor, optics, algorithm, and scene; the camera type alone does not establish task performance.
What an event stream leaves out
A pixel that sees no threshold-crossing brightness change produces no event. The stream therefore does not directly supply a complete absolute-intensity image at each instant. Sensor noise, threshold variation, background activity, and bursts caused by lighting changes also need to be handled.
Gallego and colleagues emphasise that event cameras require methods suited to their unconventional output. Converting events into frames can make existing vision software easier to reuse, but that conversion may discard some of the timing structure that motivated the sensor.
Sources
Related terms
Visual-inertial odometry
Visual-inertial odometry estimates a moving system's motion by combining camera observations with inertial measurements. It typically estimates position, orientation, velocity, and sensor biases over time.
Pose estimation
Pose estimation determines the position and orientation of an object or robot relative to a reference frame. For a rigid body in three-dimensional space, a full pose has three translational and three rotational degrees of freedom.
Sensor fusion
Sensor fusion combines information from multiple sensors or estimation sources to produce a shared estimate. The combination must account for coordinate frames, timing, uncertainty, and dependence between inputs.
Lidar
Lidar measures distance using emitted laser light and its return from surfaces. Repeated range measurements across directions can form a spatial scan or three-dimensional point cloud.