2019
DOI: 10.1109/tla.2019.8986414
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Analysis and Trends on Moving Object Detection Algorithm Techniques

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Cited by 5 publications
(3 citation statements)
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“…Other contributions of the paper include: The use of the human metric intervals, to generate a more realistic evaluation of the MODA with respect to the variations generated by human subjects when a GT is made. Comparison of state‐of‐the‐art MODA versus the human metrics intervals. Evaluation of the performance of MODA and human segmentations in a tracking task. A new methodology to evaluate MODA regarding non‐ideal interval ranges [0–1] but with human performance ranges. We considered that the BMDAs represent the best current algorithms in the literature to achieve our study because they come from an analysis of 119 dynamic object detection algorithms reported in our work [18]. These algorithms were evaluated in both their own databases and the CDnet database, and new ones reported in the references regarding motion detections algorithms [3–5].…”
Section: Introductionmentioning
confidence: 99%
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“…Other contributions of the paper include: The use of the human metric intervals, to generate a more realistic evaluation of the MODA with respect to the variations generated by human subjects when a GT is made. Comparison of state‐of‐the‐art MODA versus the human metrics intervals. Evaluation of the performance of MODA and human segmentations in a tracking task. A new methodology to evaluate MODA regarding non‐ideal interval ranges [0–1] but with human performance ranges. We considered that the BMDAs represent the best current algorithms in the literature to achieve our study because they come from an analysis of 119 dynamic object detection algorithms reported in our work [18]. These algorithms were evaluated in both their own databases and the CDnet database, and new ones reported in the references regarding motion detections algorithms [3–5].…”
Section: Introductionmentioning
confidence: 99%
“…Singha and Bhowmik [4] report a detailed review of databases and MODA for night scenarios. An analysis of tendencies of MODA, to identify the main techniques like; basic, learning dictionaries, statistical, neural networks, fuzzy logic, subspaces, robust tensors, domain transformation, is presented in a recent paper [5]. The work also evaluates the limitations of each technique and the trends regarding databases, hardware, programming language, and processing time.…”
Section: Introductionmentioning
confidence: 99%
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