Hybrid Focal Stereo Networks for Pattern Analysis in Homogeneous Scenes

TL;DR

This paper introduces a novel stereo rig system with long and short focal cameras to improve multi-camera calibration in homogeneous scenes without calibration objects, validated in indoor and crowded outdoor environments.

Contribution

It proposes a calibration method using stereo rigs with different focal lengths, eliminating the need for intrinsic variation models and enabling frequent pose re-estimation.

Findings

Effective calibration in homogeneous scenes without calibration objects

Successful validation in indoor and dense outdoor scenes

Enhanced pose re-estimation capabilities

Abstract

In this paper we address the problem of multiple camera calibration in the presence of a homogeneous scene, and without the possibility of employing calibration object based methods. The proposed solution exploits salient features present in a larger field of view, but instead of employing active vision we replace the cameras with stereo rigs featuring a long focal analysis camera, as well as a short focal registration camera. Thus, we are able to propose an accurate solution which does not require intrinsic variation models as in the case of zooming cameras. Moreover, the availability of the two views simultaneously in each rig allows for pose re-estimation between rigs as often as necessary. The algorithm has been successfully validated in an indoor setting, as well as on a difficult scene featuring a highly dense pilgrim crowd in Makkah.