FaceSpotR

We help you seek so you find what you are seeking, any time, any place, with FaceSpotR.

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Resources

FaceSpotR has been working on Image Recognition, specifically facial recognition, since 2011. FaceSpotR seeks to find solutions to some of the heart breaking challenges facing humanity, especially with missing children or adults needing special care.

FaceSpotr is working on solutions to automatically identify and alert of a potential intruder entering a facility without access.
FaceSpotR by using behavioural and psychological studies, applying pattern analysis combined with sentiment analysis does a predictive analysis to predict in real-time possible outcomes of potential scenarios with a probablity of occurance score for each scenario, all to help prevent, if not minimize the impact, of a crime to human lives.
FaceSpotR, applying image minimg and search alogorithms, seeks to help mine images of missing persons from all avaialble online sources, applying continous learning, through updates and refinement, to locate persons using a path generated through digital footprints.
Face in Video Evaluation (FIVE) was being conducted by NIST to assess the capability of face recognition algorithms to correctly identify or ignore persons appearing in video sequences.
Face Recognition Technology (FERET) was being conducted by NIST to o develop face recognition algorithms to provide automatic face recognition capabilities that could be employed to assist security, intelligence, and law enforcement personnel in the performance of their duties.
Point and Shoot Face Recognition Inexpensive "point-and-shoot" camera technology combined with social network technology motivates the general population to use face recognition technology. Users expect a lot; they want to snap pictures, shoot videos, upload, and have their friends, family and acquaintances more-or-less automatically recognized. Despite the apparent simplicity of the problem, face recognition in this context is hard. Roughly speaking, failure rates in the 4 to 8 out of 10 range are common. In contrast, error rates drop to roughly 1 in 1,000 for well-controlled imagery. To spur advancement in face and person recognition NIST created the Point and Shoot Face Recognition Challenge (PaSC).

Our Company

FaceSpotR [pronounced Face Spotter] is about empowering you to help seek what you set out to find. Our belief is there is nothing lost that cannot be found, applying the right knowledge armed with the right tools, the sought will eventually present themselves to the seeker.

About

FaceSpotR was started in 2011 to apply image and facial recognition to address some of society's key Human Life challanges. FaceSpotR is about empowering individuals and creating awareness in communities while being smart to stay safe and feel protected.

Leadership

The Leadership team at FaceSpotR combines centuries of product, industry and technology experience to create a world that is safe and protected.




Location

FaceSpotR is headquartered in Leesburg, Virginia.

Our address is,
 10 South King Street, Suite F,
 Leesburg, Virginia, 20175.
 Tel: +1-703-496-4600
 Fax: +1-703-496-4819
 Email: info@facespotr.com

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© 2011, FaceSpotR Corporation