Abstract
The novel approach to physical security based on visible light communication (VLC) using an informative object-pointing and simultaneous recognition by high-framerate (HFR) vision systems is presented in this study. In the proposed approach, a convolutional neural network (CNN) based object detection method is used to detect the environmental objects that assist a spatiotemporal-modulated-pattern (SMP) based imperceptible projection mapping for pointing the desired objects. The distantly located HFR vision systems that operate at hundreds of frames per second (fps) can recognize and localize the pointed objects in real-time. The prototype of an artificial intelligence-enabled camera-projector (AiCP) system is used as a transmitter that detects the multiple objects in real-time at 30 fps and simultaneously projects the detection results by means of the encoded-480-Hz-SMP masks on to the objects. The multiple 480-fps HFR vision systems as receivers can recognize the pointed objects by decoding pixel-brightness variations in HFR sequences without any camera calibration or complex recognition methods. Several experiments were conducted to demonstrate our proposed method’s usefulness using miniature and real-world objects under various conditions.
Highlights
Physical security using cyber-physical systems (CPS) involves numerous interconnected systems to monitor and manipulate real objects and processes
Related works In this study, we primarily focus on prototyping CNNobject detection assisted projection mapping that can encode information on the environmental object and HFR vision-based decoding while maintaining the confidentiality of data to be communicated
The proposed active projection mapping and simultaneous recognition system consists of three parts, (1) a smart object pointing using artificial intelligenceenabled camera-projector (AiCP) system as a transmitter, (2) an HFR vision-based object recognition system as a receiver, and (3) encoding and decoding protocol in visible light communication (VLC)
Summary
Physical security using cyber-physical systems (CPS) involves numerous interconnected systems to monitor and manipulate real objects and processes. The proposed active projection mapping and simultaneous recognition system consists of three parts, (1) a smart object pointing using AiCP system as a transmitter, (2) an HFR vision-based object recognition system as a receiver, and (3) encoding and decoding protocol in VLC. HFR vision acquires all the SMP-planes frame-by-frame and decodes the packets of information embedded in each frame by temporally observing each pixel in an image that corresponds to the projection area. Pixels with the same phase are segregated as a single object; the remaining pixels correspond to the non-projection area are referred to as zero-pixel value In this way, HFR vision systems can accumulate frame-by-frame data, decode the embedded information to recognize globally pointed objects, simultaneously. Informative masking The FPP and IPP images are cumulatively generated based on the detected objects and their bounding box B(Iyolo(x, y, t)) ; they are passed through the spatiotemporal encoding
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