At Vapplica Group our goal is to make facial recognition technology affordable for all types of industries. Our technology is accredited, validated and tested by National Institute of Standard and technology.
Our team went through years of research to build very distinctive and unVapplica Groupue facial recognition system that is easy to deploy with exceptional performance. It makes it easy for everyone to deploy by taking advantage of flexible pricing. Start is just hours. Get up and running fast with Vapplica Group's out-off-the-box face recognition software.
Vapplica Group Lister system provides the most effective solution in facial recognition. It is designed to extract faces in real time and matches them against the watch-list of individuals. System identifies an individual from the watch-list to raise an alert so appropriate actions can rapidly be taken to reduce the risk of public safety threats.
PARTICIPATED IN NIST FIVE PROJECT
Vapplica Group identified as F30V
Some algorithms (for example from providers A, C, D, F, L, R, Q) elect to track faces over short sub-second intervals but also report more tracks. Algorithm F30V finds many face tracks, but each face track spans an average of less than a fifth of a second. Since it typically takes a subject several seconds to walk down the PLB, the algorithm is likely breaking up the person’s journey across several face tracks.
Back in section 5.5.2 the effect of enrolling K = 3 images per subject was examined. Table 35 demonstrates that in such cases template generation time usually scales about linearly with the number of input faces. This is true in most cases, but with the exceptions of F30V, G30V, G31V, J30V, J31V, and J32V which maintain approximately constant size. This may occur because only one image is used, for example the “best” one, or because information is being fused across all K inputs, either at the image level (modeling) or at the feature level.
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