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SentiSight 3.0 Universal Object Recognition Technology Available Now From Neurotechnology
Date:8/29/2011

;The algorithm is fully tolerant of in-plane rotation, up to 15-20 degrees of out-of-plane rotation (such as from frontal to profile) and a wide range of changes in scale. It can handle occlusion of up to 50% as long as enough unique edges of the object are still visible. Multiple views can be added to the object model to provide even more reliable recognition or better out-of-plane rotation tolerance. The shape-based algorithm offers enhanced recognition at near real-time performance in many conditions.

The enhanced local-feature-based algorithm in SentiSight 3.0 offers even faster recognition for objects that have clear and stable local features, such as bank notes, brand labels on packaging, logos, etc. In addition to 30-40 times faster recognition speeds (when using a quad-core processor), the "learning" mode, where objects or images are presented to the system, now takes up to 40% less time and the model size is two times smaller. The overall quality of recognition is improved over the previous version, with a 10-30% reduction in the false rejection rate.

SentiSight's shape-based and local-feature-based algorithms can be used together to provide an even higher degree of recognition accuracy and quality when objects have both rich local features and distinguishable edges.

The new tracking algorithm in SentiSight 3.0 provides enhanced tracking of objects in front of complex backgrounds and performs automatic, reliable tracking of fast-moving objects after they have been recognized. The algorithm can track local-feature-rich as well as edge-feature-rich objects.

The SentiSight 3.0 SDK can be used for development of a wide range of applications, including:

  • Recognition of documents, stamps, labels, packaging and other items for sorting, logo masking, usage monitoring and similar applications
  • Object counting and inspection for assembly lines and other industrial applications
  • Augme
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