Dynamic estimation of the discernment frame in belief function theory: Application to object detection

Rekik, W.K.; Hégarat‐Mascle, Sylvie Le; Reynaud, Roger; Kallel, A.; Hamida, Ahmed Ben

doi:10.1016/j.ins.2015.01.039

Cited by 12 publications

(4 citation statements)

References 21 publications

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“…To manage imprecise and uncertain data (objects characteristics, set of objects, false alarms...), belief function theory is a suitable framework [39]. It has been effective in developing solutions for several problems such as data association and filtering [34], [35]. To reduce the uncertainty of objects, an evidential filtering approach has been proposed in [34].…”

Section: A Related Workmentioning

confidence: 99%

“…It has been effective in developing solutions for several problems such as data association and filtering [34], [35]. To reduce the uncertainty of objects, an evidential filtering approach has been proposed in [34]. It aims at estimating the set of objects of interest called discernment frame i.e.…”

Section: A Related Workmentioning

confidence: 99%

“…It aims at estimating the set of objects of interest called discernment frame i.e. discarding false alarms [34]. Assuming that an object reliability increases with its size and temporal persistence, evidential rules have been used to rank objects according to their reliability.…”

Section: A Related Workmentioning

confidence: 99%

See 2 more Smart Citations

A novel approach for multi-object tracking using evidential representation for objects

Rekik

Hégarat‐Mascle

Aldea

2017

2017 20th International Conference on Information Fusion (Fusion)

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Abstract-Despite many proposed solutions, multi-object tracking remains a challenging problem in complex situations involving partial occlusions and non-uniform and abrupt illumination changes. Considering modular systems, the tracking performance strongly depends on the consistency of the different blocks relatively to error features. In this work, using the Belief Function framework, we take into account the reliability and the imprecision of the object detection and location to characterize objects and to derive a reliable descriptor. Since this latter is then estimated only on safe object subparts, even in case of crosses between objects, we use a distance between descriptor robust to partial occlusion, namely the recently proposed Bin-RatioDistance. Results obtained on various actual sequences underline the interest of the proposed algorithm by outperforming the tested alternative approaches.

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Section: A Related Workmentioning

confidence: 99%

Section: A Related Workmentioning

confidence: 99%

See 1 more Smart Citation

A novel approach for multi-object tracking using evidential representation for objects

Rekik

Hégarat‐Mascle

Aldea

2017

2017 20th International Conference on Information Fusion (Fusion)

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“…As considering the case of potentially heterogeneous sources, Johan Schubert proposed a novel way to construct and evaluate alternative frames of discernment [43]. And dynamic estimation of the discernment frame in belief function theory is proposed by Wafa Rekik et al [42] which using Cartesian product whose axes correspond to elementary discernment frames dealing with the relevance of each potential hypothesis to judge and update the frame of discernment.…”

Section: Introductionmentioning

confidence: 99%

Evidential Identification of New Target based on Residual

Zheng

Zhang

Deng

2018

INT J COMPUT COMMUN

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Both incompleteness of frame of discernment and interference of data will lead to conflict evidence and wrong fusion. However how to identify new target that is out of frame of discernment is important but difficult when it is possible that data are interfered. In this paper, evidential identification based on residual is proposed to identify new target that is out of frame of discernment when it is possible that data are interfered. Through finding the numerical relation in different attributes, regress equations are established among various attributes in frame of discernment. And then collected data will be adjusted according to three mean value. Finally according to weighted residual it is able to decide whether the target requested to identify is new target. Numerical examples are used to verify this method.

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