Object recognition by 2D-to-3D registration!

Basically, this stream of work treats object recognition
in query images as a 2D-to-3D registration problem, which
aims to estimate the camera pose of a query image relative
to a 3D object model in mainly two stages as follows:
1) Identifying 2D-to-3D correspondences. A 3D model
consists of a set of 3D points, each of which is visually
characterized by some local features, called model
Features. Putative 2D-to-3D correspondences between the Figure 1. Scalable 3D object recognition. Given many 3D object
models in the database as the targets, the task is to efficiently
recognize an arbitrary number of objects appearing in each query
Image and estimate the pose for each identified object.
local features in a query image, called image features, and
the 3D points are identified by feature matching, which
is commonly accelerated by k-d tree based approximate
Nearest neighbor (ANN).

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