SparkleVision: Seeing the world through random specular microfacets

Abstract

In this paper, we study the problem of reproducing the world lighting from a single image of an object covered with random specular microfacets on the surface. We show that such reflectors can be interpreted as a randomized mapping from the lighting to the image. Such specular objects have very different optical properties from both diffuse surfaces and smooth specular objects like metals, so we design special imaging system to robustly and effectively photograph them. We present simple yet reliable algorithms to calibrate the proposed system and do the inference. We conduct experiments to verify the correctness of our model assumptions and prove the effectiveness of our pipeline.

Infrastructure-free NLoS Obstacle Detection for Autonomous Cars

“…This section covers related works and methods previously used to see past or through occlusions (non-lineof-sight (NLoS) problem) and vision based ADAS. Proposed NLoS solutions range from WiFi signals [1], to exploiting specular surfaces [30], [7] and drones [27]. Our presented work does not rely on any infrastructure, hardware or material assumptions.…”

Turning Corners into Cameras: Principles and Methods

“…In this section we describe previous non-line-of-sight (NLoS) methods. Previous methods used to see past or through occluders have ranged from using WiFi signals [1] to exploiting random specular surfaces [21,4]. In this summary, we emphasize a few active and passive approaches that have previously been used to see past occluders and image hidden scenes.…”