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首页> 外文期刊>Italian Journal of Anatomy and Embryology >A view to the future: standardizing 3D-3D superimposition for identification from next generation video surveillance systems
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A view to the future: standardizing 3D-3D superimposition for identification from next generation video surveillance systems

机译:对未来的展望:标准化3D-3D叠加,用于下一代视频监控系统的识别

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The identification of culprits from videosurveillance systems brings about relevant problems for what concerns the reliability of comparison and quantification of the degree of match between the culprit and the suspect. The actual videosurveillance give only 2D images of the culprit, which can be compared to a 3D model of the suspect’s face in 2D-3D superimposition. However, in the next future the videosurveillance systems will provide a 3D image of the filmed persons, which may allow the operator to perform 3D-3D superimposition. This study aims at exposing a pilot study based on 10 male subjects: the face from each individual underwent two acquisitions by stereophotogrammetry. On each 3D facial model, 9 landmarks (right and left: en, ex, ch: midline: se, gn, prn) were identified by VAM? software; the acquisitions of each individual were then superimposed with the models of all the other subjects in order to reduce the distance between the corresponding points. The RMS value (Root Mean Square) between the two models was then calculated. When the two superimposed models belonged to the same individual, RMS value was in mean 1.58 mm (SD: 0.61 mm), whereas when the two models were taken from different persons, the same value was 4.54 mm (SD: 2.02 mm) with a statistically significant (p0.0001). This pilot study shows that the judgment of identification based on 3D-3D superimposition may provide reliable results. The improvement specific methods of 3D-3D comparison may provide in the next future relevant advantages in this field of forensic anthropology.
机译:从视频监视系统中识别出罪魁祸首带来了相关问题,这些问题涉及到罪犯与犯罪嫌疑人之间匹配程度的比较和量化的可靠性。实际的视频监视只能提供罪魁祸首的2D图像,可以将其与2D-3D叠加的犯罪嫌疑人面部3D模型进行比较。然而,在未来的将来,视频监视系统将提供拍摄人员的3D图像,这可以使操作员执行3D-3D叠加。这项研究的目的是公开一项基于10位男性受试者的试验研究:通过立体摄影测量法对每个人的面部进行两次采集。在每个3D面部模型上,通过VAM识别了9个地标(左右:en,ex,ch,中线:se,gn,prn)?软件;然后,将每个人的获取与所有其他主题的模型叠加在一起,以缩短相应点之间的距离。然后计算两个模型之间的RMS值(均方根)。当两个叠加模型属于同一个人时,RMS值的平均值为1.58 mm(SD:0.61 mm),而当两个模型取自不同的人时,相同的值为4.54 mm(SD:2.02 mm),且具有统计学意义(p <0.0001)。这项初步研究表明,基于3D-3D叠加的识别判断可能会提供可靠的结果。 3D-3D比较的改进特定方法可能在未来的法医人类学领域提供相关优势。

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