Sliding Shapes for 3D Object detection in Depth images__ three-dimensional

Source: Internet
Author: User

Haven't written a blog for a long time. In fact, there is nothing to write yourself ... The level is limited, eh .... The robot has recently been engaged in kinematics, so the depth vision is neglected here.

However, recently saw a previous article feel very interesting, so want to take out and share with you.

The title of the article is titled "Sliding Shapes for 3D object detection in Depth Images", which means using a sliding window for object recognition in a depth image.

The effect is as follows:


The next step is the process:


Do not know why the word is so small, but should be able to see, the process is the first training of the CAD model, and then the depth map for rendering, extraction depth map features for SVM training, and finally the use of sliding window for object recognition. The total flow in fact, a listen to know and hog pedestrian recognition that a set of the same kind of, but is put into three-dimensional space, so the biggest difference is actually extracted features are what, characteristics are as follows:


His descriptors combine the point cloud, the normal, the shape and the TSDF information, the total synthesis.



The above is a sketch of the sliding window and the training model, and it looks very simple.


This is the result of the whole project after the operation of the example, can see the effect of the leverage. Example I uploaded, you can download here.

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