Abstract
In this article, we focus on the problem of depth estimation from a stereo pair of event-based sensors. These sensors asynchronously capture pixel-level brightness changes information (events) instead of standard intensity images at a specified frame rate. So, these sensors provide sparse data at low latency and high temporal resolution over a wide intrascene dynamic range. However, new asynchronous, event-based processing algorithms are required to process the event streams. We propose a fully event-based stereo three-dimensional depth estimation algorithm inspired by semiglobal matching. Our algorithm considers the smoothness constraints between the nearby events to remove the ambiguous and wrong matches when only using the properties of a single event or local features. Experimental validation and comparison with several state-of-the-art, event-based stereo matching methods are provided on five different scenes of event-based stereo data sets. The results show that our method can operate well in an event-driven way and has higher estimation accuracy.
Highlights
Three-dimensional (3-D) vision tries to investigate the 3-D information of the real word, which is a challenging problem in computer vision
We present a fully event-based stereo matching algorithm for reliable 3-D depth estimation using semiglobal matching (SGM)
We propose a fully event-based 3-D depth perception algorithm using a message passing method
Summary
Three-dimensional (3-D) vision tries to investigate the 3-D information of the real word, which is a challenging problem in computer vision. Different technologies of depth perception can generally be categorized into two groups including active and passive methods. The laser, Kinect, and time-of-flight camera are active sensors. These sensors perform remarkable result but usually suffer from limited range and outdoor sunlight condition, since light strength falls off with distance and struggles in ambient noise light. The passive methods process pairs of images and use stereo or structure from motion methods to reconstruct the depth as is done by ZED and VI-sensor. These methods usually have relative long detection range and high resolution
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