Non-rigid point set registration is the process of finding a spatial transformation that aligns two shapes represented as a set of data points. It has extensive applications in areas such as autonomous driving, medical imaging, and robotic manipulation. Now, a method has been developed to speed up this procedure.
In a study published in IEEE Transactions on Pattern Analysis and Machine Intelligence, a researcher from Kanazawa University has demonstrated a technique that reduces the computing time for non-rigid point set registration relative to other approaches.
Previous methods to accelerate this process have been computationally efficient only for shapes described by small point sets (containing fewer than 100000 points). Consequently, the use of such approaches in applications has been limited. This latest research aimed to address this drawback.
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