| /hardware/intel/common/omx-components/videocodec/libvpx_internal/libvpx/vp8/encoder/ppc/ |
| csystemdependent.c | 12 #include "vp8/encoder/variance.h"
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| /hardware/intel/common/omx-components/videocodec/libvpx_internal/libvpx/vp9/encoder/ |
| vp9_aq_variance.c | 128 variance(x->plane[0].src.buf, x->plane[0].src.stride,
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| vp9_mcomp.h | 39 // Utility to compute variance + MV rate cost for a given MV
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| /art/runtime/base/ |
| histogram-inl.h | 143 template <class Value> inline double Histogram<Value>::Variance() const {
145 // Using algorithms for calculating variance over a population:
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/distribution/ |
| PascalDistributionImpl.java | 261 * Returns the variance.
267 * @return the variance
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| ZipfDistributionImpl.java | 263 * Returns the variance.
273 * @return the variance
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| /external/opencv3/modules/cudabgsegm/src/ |
| mog2.cpp | 59 void mog2_gpu(PtrStepSzb frame, int cn, PtrStepSzb fgmask, PtrStepSzb modesUsed, PtrStepSzf weight, PtrStepSzf variance, PtrStepSzb mean, float alphaT, float prune, bool detectShadows, cudaStream_t stream);
72 const float defaultVarInit = 15.0f; // initial variance for new components
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| /external/webrtc/webrtc/modules/audio_coding/neteq/ |
| background_noise.cc | 104 // Comparing the residual variance with the input signal variance tells
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| /hardware/intel/common/libva/va/vendor/intel/ |
| va_intel_statistics.h | 41 * number of non-zero coefficients, MB variance and MB pixel average.
156 unsigned int variance; member in struct:_VAStatsStatistics16x16Intel
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| /external/libvpx/libvpx/vp9/encoder/ |
| vp9_denoiser.c | 574 // the variance to update estimate of noise in the source.
611 // Compute variance.
613 unsigned int variance = cpi->fn_ptr[bsize].vf(src_y, local
619 // average term (sse - variance = N * avg^{2}, N = 16X16) of the
621 if ((sse - variance) < thresh_sum_diff) {
626 avg_est += variance / (10 + spatial_variance);
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| vp9_rd.c | 323 // This table models the rate for a Laplacian source with given variance
327 // where r = exp(-sqrt(2) * x) and x = qpstep / sqrt(variance),
346 // with given variance when quantized with a uniform quantizer
349 // where x = qpstep / sqrt(variance).
350 // Note the actual distortion is Dn * variance.
395 // source with given variance when quantized with a uniform quantizer
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| vp9_encodeframe.c | 55 // This is used as a reference when computing the source variance for the
269 int variance; member in struct:__anon16589
360 // Set variance values given sum square error, sum error, count.
368 v->variance = (int)(256 * (v->sum_square_error -
413 // variance is below threshold, otherwise split will be selected.
414 // No check for vert/horiz split as too few samples for variance.
416 // Variance already computed to set the force_split.
421 vt.part_variances->none.variance < threshold) {
427 // Variance already computed to set the force_split.
430 // For key frame: take split for bsize above 32X32 or very high variance
[all...] |
| /external/opencv/cvaux/src/ |
| cvhmm1d.cpp | 443 // var - pointer to the variance vector of the Gaussian pdf
477 // var - two-dimensional pointer to the variance vector of the Gaussian pdf;
479 // the second dimension is indexed along the size of the variance vector
[all...] |
| /device/google/contexthub/firmware/src/algos/ |
| gyro_cal.c | 555 // Record the variance data.
624 // Output sensor variance levels to assist with tuning thresholds
629 " Gyro Variance = {%s%d.%08d, %s%d.%08d, %s%d.%08d} [rad/sec]^2\n",
637 " Accel Variance = {%s%d.%08d, %s%d.%08d, %s%d.%08d} [m/sec^2]^2\n",
645 " Mag Variance = {%s%d.%06d, %s%d.%06d, %s%d.%06d} [uT]^2\n",
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| /external/libvpx/libvpx/vpx_dsp/ |
| ssim.c | 353 // content are detected via changes in local variance and local
361 // term 1 -> uses change in scene Variance to weight error score
395 // This measures how much consistent variance is in two consecutive
396 // source frames. 1.0 means they have exactly the same variance.
421 // The reason for the variance and mean terms is the assumption that
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| /external/opencv3/modules/flann/include/opencv2/flann/ |
| kdtree_index.h | 303 * Make a random choice among those with the highest variance, and use
304 * its variance as the threshold value.
333 /* Select one of the highest variance indices at random. */
560 * compute the mean and variance at each level when building a tree.
569 * highest variance. A value of 5 works well.
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| /external/ImageMagick/ImageMagick/api/ |
| feature.html | 103 <p>GetImageFeatures() returns features for each channel in the image in each of four directions (horizontal, vertical, left and right diagonals) for the specified distance. The features include the angular second moment, contrast, correlation, sum of squares: variance, inverse difference moment, sum average, sum varience, sum entropy, entropy, difference variance, difference entropy, information measures of correlation 1, information measures of correlation 2, and maximum correlation coefficient. You can access the red channel contrast, for example, like this:</p>
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| /external/ImageMagick/www/api/ |
| feature.html | 107 <p>GetImageFeatures() returns features for each channel in the image in each of four directions (horizontal, vertical, left and right diagonals) for the specified distance. The features include the angular second moment, contrast, correlation, sum of squares: variance, inverse difference moment, sum average, sum varience, sum entropy, entropy, difference variance, difference entropy, information measures of correlation 1, information measures of correlation 2, and maximum correlation coefficient. You can access the red channel contrast, for example, like this:</p>
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| feature.php | 103 <p>GetImageFeatures() returns features for each channel in the image in each of four directions (horizontal, vertical, left and right diagonals) for the specified distance. The features include the angular second moment, contrast, correlation, sum of squares: variance, inverse difference moment, sum average, sum varience, sum entropy, entropy, difference variance, difference entropy, information measures of correlation 1, information measures of correlation 2, and maximum correlation coefficient. You can access the red channel contrast, for example, like this:</p>
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| /external/antlr/antlr-3.4/runtime/Ruby/lib/antlr3/ |
| profile.rb | 84 def variance method in class:ANTLR3.Profile.DataSet
90 sqrt( variance )
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| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/regression/ |
| OLSMultipleLinearRegression.java | 215 * <p>Calculates the variance-covariance matrix of the regression parameters.
223 * @return The beta variance-covariance matrix
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| /external/libvpx/config/arm/ |
| libvpx_srcs.txt | 325 vpx_dsp/variance.c
326 vpx_dsp/variance.h
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| /external/libvpx/config/generic/ |
| libvpx_srcs.txt | 295 vpx_dsp/variance.c
296 vpx_dsp/variance.h
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| /external/libvpx/config/mips32/ |
| libvpx_srcs.txt | 295 vpx_dsp/variance.c
296 vpx_dsp/variance.h
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| /external/libvpx/config/mips32-dspr2/ |
| libvpx_srcs.txt | 333 vpx_dsp/variance.c
334 vpx_dsp/variance.h
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