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This work was supported in part by the Ministerio de Economia y Competitividad of the Spanish Government under project TEC2010-20412 (Enhanced 3DTV).

Analysis of institutional authors

Cuevas, CarlosAuthorGarcia, NarcisoAuthor

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On the Mahalanobis Distance Classification Criterion for Multidimensional Normal Distributions

Publicated to:Ieee Transactions On Signal Processing. 61 (17): 4387-4396 - 2013-09-01 61(17), DOI: 10.1109/TSP.2013.2269047

Authors: Gallego, G; Cuevas, C; Mohedano, R; García, N

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Abstract

Many existing engineering works model the statistical characteristics of the entities under study as normal distributions. These models are eventually used for decision making, requiring in practice the definition of the classification region corresponding to the desired confidence level. Surprisingly enough, however, a great amount of computer vision works using multidimensional normal models leave unspecified or fail to establish correct confidence regions due to misconceptions on the features of Gaussian functions or to wrong analogies with the unidimensional case. The resulting regions incur in deviations that can be unacceptable in high-dimensional models. Here we provide a comprehensive derivation of the optimal confidence regions for multivariate normal distributions of arbitrary dimensionality. To this end, firstly we derive the condition for region optimality of general continuous multidimensional distributions, and then we apply it to the widespread case of the normal probability density function. The obtained results are used to analyze the confidence error incurred by previous works related to vision research, showing that deviations caused by wrong regions may turn into unacceptable as dimensionality increases. To support the theoretical analysis, a quantitative example in the context of moving object detection by means of background modeling is given.

Keywords

Background subtractionChi-squared distributionClassification algorithmsGaussian distributionKernel density-estimationLocalizationMahalanobis distanceMixtureModelMultidimensional signal processingRecognitionSurveillanceTrackingUncertainty

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Ieee Transactions On Signal Processing due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2013, it was in position 23/248, thus managing to position itself as a Q1 (Primer Cuartil), in the category Engineering, Electrical & Electronic.

From a relative perspective, and based on the normalized impact indicator calculated from World Citations provided by WoS (ESI, Clarivate), it yields a value for the citation normalization relative to the expected citation rate of: 1.66. This 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: ESI Nov 14, 2024)

This information is reinforced by other indicators of the same type, which, although dynamic over time and dependent on the set of average global citations at the time of their calculation, consistently position the work at some point among the top 50% most cited in its field:

  • Weighted Average of Normalized Impact by the Scopus agency: 1.79 (source consulted: FECYT Feb 2024)
  • Field Citation Ratio (FCR) from Dimensions: 16.4 (source consulted: Dimensions Jun 2025)

Specifically, and according to different indexing agencies, this work has accumulated citations as of 2025-06-01, the following number of citations:

  • WoS: 47
  • Scopus: 61
  • OpenCitations: 52

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 2025-06-01:

  • 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: 52 (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.
  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/19074/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 460
  • Downloads: 2,107

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 (Gallego, Guillermo) and Last Author (GARCIA SANTOS, NARCISO).