O
Object detection
benchmarking and implementation
541–543
cascade layout optimizations
538–541
classifiers cascade
533–541
future work
543
integral image calculation
526–530
normalization value generation
530–532
scaling
532–533
Objective functions
CT reconstruction
697
Octrees, Barnes Hut
n
-body algorithm via CUDA
core methods
76–77
kernel 3 optimization
81–83
kernel 4 optimization
83
On-demand volume filtering, brain connectivity reconstruction
796
One-dimensional convolutions, BigDFT code
138–139
One thread per occurrence strategy, temporal data mining
algorithmic enhancements
216–217
basic idea
215–216
lock-based compaction
217–218
lock-free compaction
218–219
One-vs-All (OVA), multiclass SVM
295–296
Open Computing Language (OpenCL)
and BigDFT
149
and facial animation
426
and GSO
23
image/video processing
background subtraction
549–550
basic problem
547
core technology
548–551
cross-correlation
561
global memory only
561–562
global memory reads
560
global/shared/coalesced memory access
562–565
implementation/evaluation
551–565
number of images
564
Pearson's correlation coefficients
551
performance evaluation
565–566
real-time video background subtraction
552–554
single kernel and I/O operations
554–555
single kernel and serial/asynchronous I/O operations
558–560
single/three kernel and I/O operations
558
LB method implementation
385–390
MDH electrostatics
55–56
and VMD
16
OpenCV
OpenEye ROCS
vs
. PAPER
32
Open Graphics Library (OpenGL)
Chaos Game algorithm
268
de-mosaicing
586
facial animation performance
424
Fractal Flames algorithm
269
and list-mode OSEM
681–682
speed-limit-sign recognition
505
tomographic image reconstruction
684
VSM
469
Open Multi-Processing (OpenMP)
facial animation performance
424–425
MRI reconstruction
720
RNA folding problem
203
SPIRiT MRI
734
Open Source Computer Vision (OpenCV), object detection
benchmarking and implementation
541–543
cascade layout optimizations
538
core algorithm
519–520
object classifier cascade structure
521–522
scaling
532–533
OpenSPARC project, gate-level simulation
356
Ordered-subsets algorithm, CT reconstruction parameters
694–695
Ordered-subsets expectation-maximization (OSEM), list-mode
challenges
681–682
image reconstruction
680–681
line-projection accuracy
688–690
tomographic image reconstruction
685
Ordered-subsets simultaneous iterative reconstruction technique (OS-SIRT)
exhaustive sampling
696–697
GPU-accelerated regularization
696
iterative CT reconstruction algorithms
700–702
method
695–696
multi-objective optimization
697–698
parameter selection interface
698–700
quality metric
698
Order-independent transparency, programmable graphics pipeline in CUDA
algorithms, implementations, evaluations
428–433
basic problem
427–428
core method
428
fixed-size A-buffer scheme
433
future work
435
multidepth test scheme
432–433
performance evaluation
433–434
pseudocode
431
system overview
428–431
Overlapping search, pattern matching acceleration
191–192
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