SHREC ’ 15 Track : Non-rigid 3 D Shape Retrieval †

  title={SHREC ’ 15 Track : Non-rigid 3 D Shape Retrieval †},
  author={Zhouhui Lian and Jinbo Zhang and Sunoh Choi and Hanan ElNaghy and Jihad El-Sana and Takahiko Furuya and Andrea Giachetti and Reto Guler and Liyuanjun Lai and Chunchun Li and Huali Li and Frederico A. Limberger and R. Martin and Rafael Umino Nakanishi and Anselmo Ramalho Pitombeira Neto and Luis Gustavo Nonato and Ryutarou Ohbuchi and Kirill Pevzner and David Pickup and P. Rosin and Andrei Sharf and Longfei Sun and Xiangping Sun and Sibel Tari and Gozde Unal and Richard C. Wilson},
Sparse features have been successfully used in shape retrieval, by encoding feature descriptors into global shape signatures. We investigate how sparse features based on saliency models affect retrieval and provide recommendations on good saliency models for shape retrieval. Our results show that randomly selecting points on the surface produces better retrieval performance than using any of the evaluated salient keypoint detection, including ground-truth. We discuss the reasons for and… CONTINUE READING


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