In case of a crime or terrorist attack, nowadays much video footage is available from surveillance and mobile cameras recorded by witnesses. While immediate results can be crucial for the prevention of further incidents, the investigation of such events is typically very costly due to the human resources and time that are needed to process the mass data for an investigation.

In this paper, we present an approach that creates a 4D reconstruction from mass data, which is a spatio-temporal reconstruction computed from all available images and video footage.

The resulting 4D reconstruction gives investigators an intuitive overview of all camera locations and their viewing directions. It provides investigators the ability to view the original video or image footage at any specific point in time. Combined with an innovative 4D interface, our resulting 4D reconstruction enables investigators to view a crime scene in a way that is similar to watching a video where one can freely navigate in space and time.

Furthermore, our approach augments the scene with automatic detections and their trajectories and enrich the crime scene with annotations serving as clues.

@inproceedings{pollok:2019:computer,
  author    = {Thomas Pollok and
               Matthias Kraus and
               Chengchao Qu and
               Matthias Miller and
               Tobias Moritz and
               Timon Urs Kilian and
               Daniel A. Keim and
               Wolfgang Jentner},
  title     = {{Computer Vision Meets Visual Analytics: Enabling 4D Crime Scene Investigation from Image and Video Data}},
  booktitle = {International Conference on Imaging for Crime Detection and Prevention ({ICDP}-2019)},
  pages     = {44--49},
  publisher = {{IET} / {IEEE}},
  year      = {2019},
  doi       = {10.1049/cp.2019.1166}
}