TY - GEN
T1 - A Survey on Training Free 3D Texture-less Object Recognition Techniques
AU - Joshi, P.
AU - Rastegarpanah, A.
AU - Stolkin, R.
PY - 2020/3/1
Y1 - 2020/3/1
N2 - Local surface feature based 3D object recognition is a rapidly growing research field. In time-critical applications such as robotics, training free recognition techniques are always the first choice as they are free from heavy statistical training. This paper presents an experimental analysis of 3D texture-less object recognition techniques that are free from any training. To our best knowledge, this is the first survey that includes experimental evaluation of top-rated training free recognition techniques on the datasets acquired by an RGBD camera. Based on the experimentation, we briefly present a discussion on potential future research directions.
AB - Local surface feature based 3D object recognition is a rapidly growing research field. In time-critical applications such as robotics, training free recognition techniques are always the first choice as they are free from heavy statistical training. This paper presents an experimental analysis of 3D texture-less object recognition techniques that are free from any training. To our best knowledge, this is the first survey that includes experimental evaluation of top-rated training free recognition techniques on the datasets acquired by an RGBD camera. Based on the experimentation, we briefly present a discussion on potential future research directions.
UR - https://ieeexplore.ieee.org/document/9363389
U2 - 10.1109/DICTA51227.2020.9363389
DO - 10.1109/DICTA51227.2020.9363389
M3 - Conference publication
BT - 2020 Digital Image Computing: Techniques and Applications (DICTA)
ER -