MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization

08/25/2020
by   Lorenzo Bertoni, et al.
1

Monocular and stereo vision are cost-effective solutions for 3D human localization in the context of self-driving cars or social robots. However, they are usually developed independently and have their respective strengths and limitations. We propose a novel unified learning framework that leverages the strengths of both monocular and stereo cues for 3D human localization. Our method jointly (i) associates humans in left-right images, (ii) deals with occluded and distant cases in stereo settings by relying on the robustness of monocular cues, and (iii) tackles the intrinsic ambiguity of monocular perspective projection by exploiting prior knowledge of human height distribution. We achieve state-of-the-art quantitative results for the 3D localization task on KITTI dataset and estimate confidence intervals that account for challenging instances. We show qualitative examples for the long tail challenges such as occluded, far-away, and children instances.

READ FULL TEXT

page 2

page 7

page 9

page 10

page 11

06/14/2019

MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation

We tackle the fundamentally ill-posed problem of 3D human localization f...
03/09/2022

ChiTransformer:Towards Reliable Stereo from Cues

Current stereo matching techniques are challenged by restricted searchin...
12/03/2021

SGM3D: Stereo Guided Monocular 3D Object Detection

Monocular 3D object detection is a critical yet challenging task for aut...
09/01/2020

Perceiving Humans: from Monocular 3D Localization to Social Distancing

Perceiving humans in the context of Intelligent Transportation Systems (...
06/04/2019

Triangulation Learning Network: from Monocular to Stereo 3D Object Detection

In this paper, we study the problem of 3D object detection from stereo i...
11/15/2020

BirdSLAM: Monocular Multibody SLAM in Bird's-Eye View

In this paper, we present BirdSLAM, a novel simultaneous localization an...
12/20/2016

Detecting Unexpected Obstacles for Self-Driving Cars: Fusing Deep Learning and Geometric Modeling

The detection of small road hazards, such as lost cargo, is a vital capa...