In recent years, Sparse Representation (SR) and Dictionary Learning (DL) have emerged as powerful tools for efficient processing image and video data in non-traditional ways. An area of promise for these theories is object recognition. In this chapter, we review the role of algorithms based on SR and DL for object recognition. In particular, supervised, unsupervised, weakly supervised, nonlinear kernel-based, convolutional sparse coding and analysis DL methods are reviewed.
|Original language||English (US)|
|Title of host publication||Handbook of Convex Optimization Methods in Imaging Science|
|Publisher||Springer International Publishing|
|Number of pages||131|
|State||Published - Jan 1 2017|
All Science Journal Classification (ASJC) codes
- Computer Science(all)