Detecting shadows and low-lying objects in indoor and outdoor scenes using homographies

Many computer vision applications apply background suppression techniques for the detection and segmentation of moving objects in a scene. While these algorithms tend to work well in controlled conditions they often fail when applied to unconstrained real-world environments. This paper describes a system that detects and removes erroneously segmented foreground regions that are close to a ground plane. These regions include shadows, changing background objects and other low-lying objects such as leaves and rubbish. The system uses a set-up of two or more cameras and requires no 3D reconstruction or depth analysis of the regions. Therefore, a strong camera calibration of the set-up is not necessary. A geometric constraint called a homography is exploited to determine if foreground points are on or above the ground plane. The system takes advantage of the fact that regions in images off the homography plane will not correspond after a homography transformation. Experimental results using real world scenes from a pedestrian tracking application illustrate the effectiveness of the proposed approach

Radar and RGB-depth sensors for fall detection: a review

This paper reviews recent works in the literature on the use of systems based on radar and RGB-Depth (RGB-D) sensors for fall detection, and discusses outstanding research challenges and trends related to this research field. Systems to detect reliably fall events and promptly alert carers and first responders have gained significant interest in the past few years in order to address the societal issue of an increasing number of elderly people living alone, with the associated risk of them falling and the consequences in terms of health treatments, reduced well-being, and costs. The interest in radar and RGB-D sensors is related to their capability to enable contactless and non-intrusive monitoring, which is an advantage for practical deployment and users’ acceptance and compliance, compared with other sensor technologies, such as video-cameras, or wearables. Furthermore, the possibility of combining and fusing information from The heterogeneous types of sensors is expected to improve the overall performance of practical fall detection systems. Researchers from different fields can benefit from multidisciplinary knowledge and awareness of the latest developments in radar and RGB-D sensors that this paper is discussing

The Extragalactic IR Background

Current limits on the intensity of the extragalactic infrared background are consistent with the expected contribution from evolving galaxies. Depending on the behaviour of the star formation rate and of the initial mass function, we can expect that dust extinction during early evolutionary phases ranges from moderate to strong. An example of the latter case may be the ultraluminous galaxy IRAS F$10214 + 4724$. The remarkable lack of high redshift galaxies in faint optically selected samples may be indirect evidence that strong extinction is common during early phases. Testable implications of different scenarios are discussed; ISO can play a key role in this context. Estimates of possible contributions of galaxies to the background under different assumptions are presented. The COBE/FIRAS limits on deviations from a blackbody spectrum at sub-mm wavelengths already set important constraints on the evolution of the far-IR emission of galaxies and on the density of obscured (``Type 2'') AGNs. A major progress in the field is expected at the completion of the analysis of COBE/DIRBE data.Comment: 1994, invited review to be published in the Proc. of the Internatinal Conf. "Dust, Molecules and Backgrounds: from Laboratory to Space", Capri (NA), Italy, 12--15 September, 1994, in press. Tex file, 16 pages, 6 figures not included. ASTRPD-94-10-0