so what's the importance of the 3D bounding box
@Bladerskb ? you just need to know where you cannot drive on your side of the obstacle, who cares how is it shaped on the other sides anyway (in other words you can skin this cat in other ways). and they do this with driveable space, the bounding boxes are just for information more or less and it's possible though unlikely) that they can do 3D bounding boxes, there's depth information, just no orientation vector to draw the 3d part.
Show us 3D planned path prediction or driveable space prediction from other vendors if you have the samples? Those seem to be pretty important things.
This will be a rehash from reddit but i will try to update with greater details.
Actually 3D bounding box might be the most important thing in object detection. A 2d bounding box (which includes shapes) doesn't include important information which you need. For example the precise orientation of a car, with that you can predict its actions. This is vital in a dense environment, during parking, in a parking lot. Is this car trying to pull out or not. What precise direction is he pulling to, With just the information necessary to produce 2d bounding box, you don't see it. But the information is reflected in the information necessary to produce a 3d bounding box. Information like, is this the left side of a car, the door might pop out, is the door currently open? is this car trying to complete a turn. is this car coming at me or... the list goes on. As Mobileye Amon says. 2d bounding box is irrelevant.
While its impressive that distances and speed are done by visual. Mobileye has been doing this since eyeq3. There's no tangible difference between atleast the firmware you have unraveled versus what eyeq3 has been doing since 2014 production date.
I'm just laying out that the lack of 3d boxes and the instability of the detection shows their weakness compared to mobileye.
so what's the importance of the 3D bounding box
@Bladerskb ? you just need to know where you cannot drive on your side of the obstacle, who cares how is it shaped on the other sides anyway (in other words you can skin this cat in other ways).
3d bounding box whether you are using lider or camera gives you the precise orientation of an object with which you can deduce its precise moment to moment decision. This is very important in dense traffic or parking lot.
Imagine if you painted inside of the 2d boxes with solid color and then look at it in the perspective as a human. Notice how you lose all indication of what's going on in the scene, only that there are objects in front of you but no idea the scenario, orientation or state they are in.
oh wait, you already did that.
Notice how you don't know if the car infront of you is turning and where they are turning to or not. Or even if they are going the same direction as you. you're basically driving blind.
This is even now more evident when you are driving on dense surface streets. A car could be in-front of you at a intersection in the adjacent turning lane, preparing to turn into the parallel lane next to you. With a 2d bounding box info, you won't know if that car is driving forward parallel to you or driving forward adjacent to you or making a turn.
Ask yourself, can you drive in dense traffic with the above view superimposed to your view? Answer is absolutely not. You need to know the orientation of cars.
and they do this with driveable space
If only driving were just about not hitting things and not prediction, knowing and planning around the actions or perceived actions of another driver.
, the bounding boxes are just for information more or less and it's possible though unlikely) that they can do 3D bounding boxes, there's depth information, just no orientation vector to draw the 3d part.
Depth info by itself won't be useful, like a raw lidar data, depth info is simply just pixels and raw lidar data is simply a bunch of cloud points. Its when you process the info to produce quantifiable output that matters and based on your statements those outputs currently doesn't exist.
Show us 3D planned path prediction or driveable space prediction from other vendors if you have the samples? Those seem to be pretty important things.
Will provide more in another post.
