More digital forensic decision makers are prioritizing improved investigation efficiencies in 2024. The adoption of targeted collection capabilities makes sense for investigators needing to streamline investigations and reduce case backlogs. Extracting and analyzing images and videos can slow down investigations under the weight of thousands of photos or videos in mobile, cloud, or drone extractions.
As facial identification evolved well beyond facial composites and sketches, solutions were needed. As a result, the ability to target extraction and customize analysis of images and videos offers time-saving and brain-saving benefits to law enforcement and enterprise investigations.
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Targeted facial and image collection are more important than ever
Technological factors that have fueled the increased impact of digital imagery and facial identification in investigations include the rise in closed-circuit television and security video capabilities worldwide. The spread of camera surveillance increases the instances in which more persons of interest are captured during the incident or on the way to or leaving the scene. While the availability of more images and video provides more evidence for investigations, the time and resources needed to sort through increasing collections can become a challenge. Identifying images in a criminal or civil investigation is extremely time-consuming. A single case can contain thousands of images, many of which are not relevant to the investigation. A manual examination of these images, even with a thumbnail gallery, can take days.
Targeted evidence collection using facial recognition
Investigators can increase efficiency by customizing searches by frames, establishing face sets, and managing similarity ratings to leave out images that aren’t relevant. The image can be run against available image sets such as individuals recently arrested for the same offense, most wanted fugitives, or even missing persons, including children.
Extracting images or videos relevant to an investigation starts the forensic facial process. The following capabilities can add efficiency to the case and others:
- Investigators should have the ability to adjust the search time of video by frame, identifying the face of a suspect or person of interest.
- Investigators should have the ability to compare faces recognized with any other data and face sets shared with authorized
- Cold case leads can be generated by faces recognized in unrelated cases or unrelated devices.
- Following extraction from a device or the cloud, facial recognition tools can identify faces of unknown individuals within a device and compare them to other devices, while searching the contents of the same device.
Today’s investigators need image and facial tools
Efficiency can best be realized using digital forensic platforms that include built-in tools capable of pulling all of the faces or facial data in every video and put into a face set or collection of templates and running it against all other data sets. The result is faster analysis of images you do need and less time spent on the evidence you don’t need.
Efficiencies using facial categorization
Facial categorization further fine-tunes analysis. If evidence is collected in the form of images or video from security cameras, facial recognition will identify and map every individual face collected in the interface. Built-in digital forensic tools should enable investigators to categorize those human faces. Categorization can include detailed face analytics such as gender, race, and age.
All facial and image categorization capabilities are not equal. Because many law enforcement and government investigations are done in secure units without internet connection, facial and image recognition capabilities can be lost. Built-in tools performing complete facial and image categorization locally on a computer allows face sets to be run against an uploaded face set to obtain matches.
Efficiencies using image categorization
Investigators will benefit from image categorization that aids analysis in an investigation. These classifications might include pornography, child sexual abuse material, extremism, drugs, alcohol, and weapons. Investigators can select all or selected categories or fine-tune the positive hit settings. Then review the tagged data and exclude any false positives.
Brain-saving settings reduce mental toll
Tagging images and videos investigators don’t want to view can also provide long-term mental health benefits. Tools providing “brain-saving” capabilities empower investigators to reduce the mental toll by hiding thumbnails of disturbing images and videos determined to not be relevant to their case.
Better built-in tools for more efficient image collection and analysis
Built-in facial and video recognition capabilities must give investigators the ability to find matches faster using targeted extractions and powerful facial search tools. These capabilities are crucial to improving the efficiency of investigators sorting through thousands of images and videos while still finding the evidence and analysis they need.