Lucida: Enhancing the Creation of Photography Through Semantic, Sympathetic, Augmented, Voice Agent Interaction

We present a dynamic framework for the integration of Machine Learning (ML), Augmented Reality (AR), Affective Computing (AC), Natural Language Processing (NLP) and Computer Vision (CV) to make possible, the development of a mobile, sympathetic, ambient (virtual), augmented intelligence (Agent). For this study we developed a prototype agent to assist photographers to enhance the learning and creation of photography. Learning the art of photography is complicated by the technical complexity of the camera, the limitations of the user to see photographically and the lack of real time instruction and emotive support. The study looked at the interaction patterns between human student and instructor, the disparity between human vision and the camera, and the potential of an ambient agent to assist students in learning. The study measured the efficacy of the agent and its ability to transmute human-to-Human method of instruction to human-to-Agent interaction. This study illuminates the effectiveness of Agent based instruction. We demonstrate that a mobile, semantic, sympathetic, augmented intelligence, ambient agent can ameliorate learning photography metering in real time, ‘on location’. We show that the integration of specific technologies and design produces an effective architecture for the creation of augmented agent-based instruction.