Modulated Acquisition of Spatial Distortion Maps

Abstract

This work discusses a novel approach to image acquisition which improves the robustness of captured data required for 3D range measurements. By applying a pseudo-random code modulation to sequential acquisition of projected patterns the impact of environmental factors such as ambient light and mutual interference is significantly reduced. The proposed concept has been proven with an experimental range sensor based on the laser triangulation principle. The proposed design can potentially enhance the use of this principle to a variety of outdoor applications, such as autonomous vehicles, pedestrians' safety, collision avoidance, and many other tasks, where robust real-time distance detection in real world environment is crucial.

Robust Depth Image Acquisition Using Modulated Pattern Projection and Probabilistic Graphical Models

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The image acquisition procedure uses specialized hardware (comprised of a laser projector and a high-speed camera) to project a structured light pattern onto the target scene with the goal of capturing an image of the distorted pattern (i.e., a spatial distortion map). The procedure is based on the recently-introduced concept of modulated pattern projection [31,34], which ensures that spatial distortion maps of good quality can be captured in challenging conditions; for example, in the presence of strong incident sunlight or under mutual interference caused by other similar sensors directed at the same scene.

The light plane-labeling procedure establishes the correspondence between all parts of the projected light pattern and the detected pattern that has been distorted due to the interaction with the target scene. The procedure uses loopy-belief-propagation inference over probabilistic graphical models (PGMs) as proposed in [33] to solve the correspondence problem and, differently from other existing techniques in the literature, exploits spatial relationships between parts of the projected pattern, as well as temporal information from several consecutive frames to establish correspondence.…”

“…The procedure is based on the recently-introduced concept of modulated pattern projection [31,34], which ensures that spatial distortion maps of good quality can be captured in challenging conditions; for example, in the presence of strong incident sunlight or under mutual interference caused by other similar sensors directed at the same scene.…”

“…The section starts by presenting the hardware setup used in the sensor and then proceeds by describing the pattern acquisition procedure and its characteristics. Note that the underlying concept of the acquisition procedure was originally introduced in [31]. …”

“…This paper addresses the problem of outdoor depth imaging with structured light approaches and presents a novel sensor designed specifically for outdoor deployment [30]. The sensor exploits the recently-proposed concept of modulated pattern projection, introduced by our group in [31], which facilitates the acquisition of spatial distortion maps in real-world environments (even in the presence of strong incident sunlight), where other existing approaches often fail or at least struggle with their performance. Correspondences between the projected pattern and the acquired distortion map are established based on a novel probabilistic approach relying on graphical models (inspired by [32,33]) and are used in conjunction with prerecorded reference frames to compute the depth information for each point of the projected structured light pattern.…”

Design of Spreading-Codes-Assisted Active Imaging System

“…These methods are efficient in controlled disturbance-free environments. The lack of cost-efficient and robust solutions suitable for work in real-world environments motivated our prior work [3,4], where we introduced the concept of modulated acquisition of spatial distortion maps -snapshots of multi-line patterns projected onto the object. These patterns can be converted to 3D mesh according to the laser triangulation [5] principle as depicted in Figure 1: the distance to the point O(x,y,z) belonging to the pattern's projection at the object's surface is calculated from fixed parameters of the detector (focal length f, base line b between the optical centre of the lens and the laser source, angle α between the base line and the plane of the projected light) and the position of point P (v,u) Thus, distance detection in this method relies on determining the coordinates of the illuminated pixels and the index of line (i.e., angle α) they belong to.…”