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Computer Vision 3D Flow and Function AI with LiDAR
Introduction Solution overview Partner overview Architecture overview Sizing and scaling Use case validation Conclusions
Conclusions
References

Conclusions

Home > Workload Solutions > Computer Vision > White Papers > Computer Vision 3D Flow and Function AI with LiDAR > Conclusions

Conclusions

  • We have conducted extensive tests with the SENSR product deployed on the Dell Technologies Validated Design for Computer Vision platform. This paper describes our investigation of how LiDAR can provide a more complete understanding of how people and objects flow and function within public and private spaces. Our results show that LiDAR has some unique capabilities that are not available with traditional camera systems. We also documented our findings of the resource requirements when running LiDAR workloads on our CV platform. The outcomes are:

    • We showed "Tag and Follow" capabilities that track an object (such as a person or car) across multiple different LiDAR sensors.
    • The SENSR software suite runs seamlessly in our virtualized environment and processes LiDAR data reliably.
    • The solution is scalable and can be expanded as new LiDAR sensors are added to the system.
    • SENSR provides an SDK that can be used to integrate event data with external tools (such as a VMS).