Potential of embedded vision platforms in development of spatial AI enabled CPS

Motivated by the recent trends in the field of em-bedded vision platforms, we discuss potential of such solutions in providing foundations for the next generation of Cyber-Physical Systems (CPS). Improved capabilities and reduced price of these platforms will have profound effect on their everyday usage and applications. In comparison to speech and natural language processing, which have established speech recognition and machine translation applications as indispensable in many contemporary CPSs, the vision community is still searching for an application that would be so necessary and desirable to make most of the consumers buy specific vision hardware just to run it. That would be the ultimate proof of the core value of the technology in the market. Thus, also vision problems come with a longstanding tradition and history of numerous solutions, it is still hard to point out a single application that would incorporate many specific vision tasks into one device, and which would be ubiquitously useful and affordable to all (e.g. like smartphone has done in the fields of communication and personal computing). However, with development of new miniaturization technologies and spatial AI it is reasonable to expect that there will be more possibilities for designing CPS with capabilities of visual understanding of outdoor, dynamic and uncontrolled environments. One step in such direction are embedded vision platforms that besides powerful computing capabilities also provide multimodal perception, and thus improve the algorithm performance. As an example, we will discuss stereo depth perception in the context of new spatial AI platforms like OAK-D lite, and point out some possibilities for its improvement and integration into future CPS.