Neurotechnology, a provider of high-precision biometric and object identification technologies, recently announced the availability of SentiSight 2.0 SDK universal object recognition technology for the development of robotics, artificial intelligence and computer-based vision applications.
The SentiSight 2.0 algorithm provides enhanced 2D and 3D object recognition quality using still or video images from most digital cameras, including Webcams. Among the new features is the ability to find and count the number of objects in a scene and the ability to compare and identify pictures even when the perspective has changed. The algorithm is tolerant to scale, rotation and pose under a variety of image conditions, providing the versatility required for wide range of computer and machine vision applications, from manufacturing and security systems to Web-based image search engines. Because SentiSight can process video streams in real time, it is suitable for use in autonomous robot navigation, assembly line parts recognition and other applications that require fast and accurate real-time identification.
The new solution enables fully automatic and manual object learning as well as simultaneous multiple object detection and recognition. Used in conjunction with a digital camera or other visual input device, the algorithm enables a computer or robot to "learn" 2D and 3D objects or a series of objects in a scene by extracting specific features and object descriptors from different sides, distances and angles. SentiSight then develops an object model that can be stored in a database. Later, when presented with an image or scene from a live camera, still image or video stream, the algorithm can detect whether a particular object is in the scene, identify where the object is located and even count the number of objects in the scene.
SentiSight 2.0 supports both Microsoft Windows and Linux operating systems and gives developers complete control over SDK data input and output, enabling the functions to be used with most cameras.
For more information, visit http://www.neurotechnology.com
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