- This algorithm, supported by scientific publications, automatically estimates both the focal length of the camera and the distance at which the photo was taken together with the orientation of the subject with respect to the camera.
- Once a set of cephalometric (2D, photo) and craniometric (3D, skull) landmarks have been located, and after selecting or defining a soft tissue thickness study, our automatic overlapping algorithm will find the best possible overlap in tenths of a second.
Unique technology that automates the most subjective and
error-prone task, the skull-face overlay.
* x100 slow simulation of the internal process of the automatic overlapping algorithm
Automation of processes of comparison of multiple skulls and photos for forensic files corresponding to scenarios of mass graves, mass disasters and candidate searches on databases of missing persons/osteologists.
- Define landmarks, landmark pairs and soft-tissue thickness to be used.
- User management with different roles inside the institution.
- Creation of databases with AM and PM records, photos and 3D models.
- Creation of forensic files from subsets of AM and PM data.
- Identification reports with heterogeneous data (text, tables, images).
(meets European standard MEPROCS)
A software that provides tools that facilitate the correct location of 2D (grid, reference lines) and 3D landmarks (frankfurt, coronal and sagittal planes), the editing of soft tissue direction and thickness and the analysis of morphological correspondence using transparency and wipe functions.
- Skull (3D) - face (2D) overlap using tools for rotation, translation, scaling and projection of the 3D model.
- Advanced operations (coupled and uncoupled): change of camera-subject distance, focal distance and main point.
Pay according to the use, free for educational and research purposes. Always work with the latest version.
You only need a browser and internet, in any terminal or operating system, from anywhere in the world.
Work in a network, share cases with other experts and institutions or offer your services to other institutions.
Participate in research studies or look for volunteers for yours. Discuss with other researchers the latest scientific advances, such as applying specific methods, etc.
Confidentiality and security are assured, storage and transmission of encrypted data.
In collaboration with the University of Granada we are working on incorporating new scientific achievements:
- Quantitative evaluation of morphological correspondences and decision support system. This system is capable of assigning a quantitative evaluation to each case of craniofacial superimposition and, therefore, sort listing (and filtering) an unlimited number of candidates for a given skull or person.
- Automatic location of cephalometric landmarks in photos and cranemometrics in 3D models of the skull.
- Positioning and articulation of the mandible with the rest of the skull automatically depending on the photograph.
- Automatic assembly of fragmented skulls
- Automatic generation of case reports: tables, images and summaries in text format automatically generated in order to facilitate the decision making in legal proceedings
Probability that the correct correspondence of a case will appear in a list of the best R's, where R denotes the ranking.
Preliminary results of the automatic decision support system.
C. Campomanes Alvarez, R Martos-Fernández, C. Wilkinson, O. Ibáñez and O. Cordón. Lodeling skull-face anatomical/morphological correspondence for craniofacial superposition-based identification. IEEE Transactions on Information Forensics and Security 13:6 (2018) 14
We are working on new modules that turn Skeleton-ID into an integral tool that allows to analyze all available AM and PM information.
In collaboration with the University of Granada we have patented a fully automatic and highly accurate identification system for certain bone structures by means of comparison of X-rays and 3D models of bones. We are collaborating in a large-scale study to confirm these magnificent results. The next step will be to develop and integrate this system as another Skeleton-ID module.