Dilated Convolution for Time Series Learning
Wang Zhang, Subhro Das, et al.
ICASSP 2025
We address the problem of constructing view aspects of 3D free-form objects for efficient matching during recognition. We introduce a novel view representation based on "shape spectrum" features, and propose a general and powerful technique for organizing multiple views of objects of complex shape and geometry into compact and homogeneous clusters. Our view grouping technique obviates the need for surface segmentation and edge detection. Experiments on 6,400 synthetically generated views of 20 free-form objects and 100 real range images of 10 sculpted objects demonstrate the good performance of our shape spectrum based model view selection technique. © 1997 IEEE.
Wang Zhang, Subhro Das, et al.
ICASSP 2025
Amarachi Blessing Mbakwe, Joy Wu, et al.
NeurIPS 2023
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ken C.L. Wong, Satyananda Kashyap, et al.
Pattern Recognition Letters