Feature Recognition and Data Analysis Strategy for Touch Screen Objects Based on Camera Array

Feature recognition and data analysis strategy for touch screen objects based on camera array is proposed to solve the problems of high cost of large-screen visualization platform and low accuracy of screening the feature attributes of touch-screen objects. The strategy constructs a touch screen object feature attribute model, which contains five sub-models: static feature attribute model, single screen bottom feature attribute model, overall bottom surface feature attribute model, stereoscopic feature attributes model and dynamic feature attribute model. Multi-screen stitching algorithm, recognition efficiency algorithm and recognition accuracy algorithm for touch screen objects are designed to make the recognition of touch screen objects more efficient and the recognition accuracy rate increasing. The strategy can well assist users to improve system performance and provide comprehensive support for building business systems with large screens and visualized interactive systems.