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Analysis of institutional authors

Carrio, AdrianCorresponding AuthorBavle, HridayAuthorCampoy, PascualAuthor

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June 9, 2019
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Attitude estimation using horizon detection in thermal images

Publicated to:International Journal Of Micro Air Vehicles. 10 (4): 352-361 - 2018-12-01 10(4), DOI: 10.1177/1756829318804761

Authors: Carrio, Adrian; Bavle, Hriday; Campoy, Pascual

Affiliations

Univ Politecn Madrid, Comp Vis & Aerial Robot Grp, CSIC, Madrid, Spain - Author

Abstract

The lack of redundant attitude sensors represents a considerable yet common vulnerability in many low-cost unmanned aerial vehicles. In addition to the use of attitude sensors, exploiting the horizon as a visual reference for attitude control is part of human pilots' training. For this reason, and given the desirable properties of image sensors, quite a lot of research has been conducted proposing the use of vision sensors for horizon detection in order to obtain redundant attitude estimation onboard unmanned aerial vehicles. However, atmospheric and illumination conditions may hinder the operability of visible light image sensors, or even make their use impractical, such as during the night. Thermal infrared image sensors have a much wider range of operation conditions and their price has greatly decreased during the last years, becoming an alternative to visible spectrum sensors in certain operation scenarios. In this paper, two attitude estimation methods are proposed. The first method consists of a novel approach to estimate the line that best fits the horizon in a thermal image. The resulting line is then used to estimate the pitch and roll angles using an infinite horizon line model. The second method uses deep learning to predict attitude angles using raw pixel intensities from a thermal image. For this, a novel Convolutional Neural Network architecture has been trained using measurements from an inertial navigation system. Both methods presented are proven to be valid for redundant attitude estimation, providing RMS errors below 1.7 degrees and running at up to 48 Hz, depending on the chosen method, the input image resolution and the available computational capabilities.

Keywords

Attitude estimationConvolutional neural networkDeep learningHorizon detectionThermal imageUnmanned aerial vehicleVision

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal International Journal Of Micro Air Vehicles due to its progression and the good impact it has achieved in recent years, according to the agency Scopus (SJR), it has become a reference in its field. In the year of publication of the work, 2018, it was in position , thus managing to position itself as a Q2 (Segundo Cuartil), in the category Aerospace Engineering. Notably, the journal is positioned en el Cuartil Q3 for the agency WoS (JCR) in the category Engineering, Aerospace.

From a relative perspective, and based on the normalized impact indicator calculated from the Field Citation Ratio (FCR) of the Dimensions source, it yields a value of: 2.92, which indicates that, compared to works in the same discipline and in the same year of publication, it ranks as a work cited above average. (source consulted: Dimensions Jul 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-07-05, the following number of citations:

  • WoS: 12
  • Scopus: 16
  • Google Scholar: 14

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-05:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 22 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • The work has been submitted to a journal whose editorial policy allows open Open Access publication.

Leadership analysis of institutional authors

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Carrió Fernández, Adrián) and Last Author (CAMPOY CERVERA, PASCUAL).

the author responsible for correspondence tasks has been Carrió Fernández, Adrián.