SentiSight is designed to be as universal as possible and is able to perform fully automatic and manual object learning. SentiSight has two operation modes: learning and recognition. In learning mode, the SentiSight algorithm creates an object model by extracting object features from an image or video. In recognition mode, SentiSight finds and tracks objects with features matching those previously stored in object models. SentiSight is designed to be as universal as possible and is able to perform fully automatic or manual object learning. The technology can be used for a wide range of tasks, including: Some of the potential applications for SentiSight include security systems, vision systems for robots, machine vision (like parts recognition in production lines), search engines that recognize objects in picture files, road signs recognition, etc. 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 Augmented and extended reality applications for toys, games, devices and Web applications such as: smart toys for children that recognize cards, images, pictograms, etc.; recognition of places based on photographs; recognition of products such as beverages, foods and other consumer goods. Robotic vision for navigation and manipulation, Law enforcement applications for identification, such as tattoo recognition.
Nov 07, 2018
Eye Iris SDK > SentiSight SDK