Handbook of Geometric Computing: Applications to Pattern Recognition, Computer Vision, Neural Computing, and Robotics Book

1	Spatiotemporal dynamics of visual perception across neural maps and pathways	3
2	Symmetry, features, and information	31
3	Geometric approach to multilayer perceptrons	69
4	A lattice algebraic approach to neural computation	97
5	Eigenproblems in pattern recognition	129
6	Geometric framework for image processing	171
7	Geometric filters, diffusion flows, and kernels in image processing	203
8	Chaos-based image encryption	231
9	One-dimensional retinae vision	269
10	Three-dimensional geometric computer vision	305
11	Dynamic P[superscript n] to P[superscript n] alignment	349
12	Detecting independent 3D movement	383
13	Robot perception and action using conformal geometric algebra	405
14	Uncertainty modeling and geometric inference	461
15	Uncertainty and projective geometry	493
16	The tensor voting framework	535
17	Methods for nonrigid image registration	571
18	The design of implicit functions for computer graphics	603
19	Grassmann-Cayley algebra and robotics applications	629
20	Clifford algebra and robot dynamics	657
21	Geometric methods for multirobot optimal motion planning	679
22	The computation of reachable surfaces for a specified set of spatial displacements	709
23	Planning collision-free paths using probabilistic roadmaps	737