About the Selectr Technology
Thousands of images flow into your editorial system every day and grow into a confusing and often seemingly impenetrable thicket of media data. In addition, there is usually inconsistent, incomplete and sometimes also incorrect tagging of the photos, as well as language barriers with regard to text descriptions or legends. A selective search for the right image motif is thus enormously difficult and very time consuming, resulting in a high loss rate. However, the rapidly growing amount of digital media data makes it too resource-consuming to perform a full and qualitative content-related capture of all data manually.
Leave this work to PAMA Selectr's intelligent algorithms and increase the quality of your metadata and thus fundamentally the quality of your own services. Our technology enables intelligent and automated extraction of information from images and videos, and ensures that your media can quickly be tagged and retrieved at any time, whether they have 10,000 or 10 million images.
Through automated content-based tagging, our technology allows you to enrich existing image information, allowing you to specify your search in a way never seen before. With PAMA Selectr you will always find the right image or the right media file!


Features
By increasing data quality at the meta level, we enable the detection of:
Faces (celebrities, politicians, athletes)
Person composition (number of people in the picture)
Logos and brands
Image orientation (portrait, landscape, square)
Face orientation (profiles, frontal)
Style (Color Photo, B/W, Indoors, Outdoors)
Gesture and attitude
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Looks at the camera
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Speaks into the microphone
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Handshaking
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Duel (football)
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Gesturing
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Celebrating
Through our NLP (Natural Language Processing) technology, we also enable the detection of:
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Organizations
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Places
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IPTC categories (based on the product description)
The Selctr technology also allows:
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Image clustering by topic and/or event
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Recognition of semantic structures
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Complex search queries
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Overcoming of language barriers, e.g. through similarity search