Hi. I am working on 6DoF object pose estimation based on RGBD recently for som household stuff, such as cola can, water bottle … I have done a lot of researches, but I didn’t find a proper methods available on Nano platform as for the computin cost.
They are usually a registration problem from key points between the rgbd observation of object and CAD model. Even for the categorical level methods, a huge memory needed for the point cloud processing.
Are there some methods that could deploy to Jetson Nano? Nowadays, I turned my concerntration from deep learning based models to classical 3D descriptors, such as SHOT and CVFH. If you have experiences which can be deployed on a Nano, please give me a brief introduction. Thanks.