In this paper, we use gray, Gabor, local binary pattern (LBP) [15] [16], multiresolution local binary pattern (MLBP) [17], local Gabor binary pattern (LGBP) [18], and multi-resolution local Gabor binary pattern (MLGBP) approaches to extract the features of each facial image.
Sample text:```Over the last few years, many different local interest point detectors (like Harris3D [16], Cuboid [6], Hessian [35] or Dense sampling [33]) and many spatio-temporal descriptors (like HOG [17], HOG3D [14], HOF [17], Cuboid [6] or ESURF [35]) have been proposed.```
Sample intent: method
Sample text:```(orb), egl, and BicD (Costa et al., 2005; Mach and Lehmann, 1997; Suter and Steward, 1991).```
Sample intent: method



Sample text:```These are in keeping with earlier studies on the steadystate response (2, 5, 8), step-function response, (3, 5, 6, 14) and sinusoidal response ( 14) of the various vascular beds.```
Sample intent: result



Sample text:```…(LING)] thalamus (THA), as well as limbic/paralimbic regions [e.g. insula, superior temporal pole and inferior orbitofrontal cortex] (Table 2), which is in accordance with previous findings on functional brain networks constructed using resting-state fMRI (Achard et al., 2006; He et al., 2009b).```
Sample intent: result



Sample text:```Following past work, we show that such basis models can be learned from 2D annotations using techniques adapted from nonrigid structure from motion (SFM) [20, 19].```
Sample intent: method



Sample text:```In this study, we generalized previous results regarding the quasi-Gaussian shape and the scalar property using the SBF model [13,21,52].```
Sample intent: result
Sample text:```In the first pass, we display the diffuse lobe of the BRDF through spherical harmonic environment map rendering [Ramamoorthi and Hanrahan 2001].```
Sample intent: background



Sample text:```(orb), egl, and BicD (Costa et al., 2005; Mach and Lehmann, 1997; Suter and Steward, 1991).```
Sample intent: method



Sample text:```In this study, we generalized previous results regarding the quasi-Gaussian shape and the scalar property using the SBF model [13,21,52].```
Sample intent: result



Sample text:```Following past work, we show that such basis models can be learned from 2D annotations using techniques adapted from nonrigid structure from motion (SFM) [20, 19].```
Sample intent: method



Sample text:```Over the last few years, many different local interest point detectors (like Harris3D [16], Cuboid [6], Hessian [35] or Dense sampling [33]) and many spatio-temporal descriptors (like HOG [17], HOG3D [14], HOF [17], Cuboid [6] or ESURF [35]) have been proposed.```
Sample intent: method



Sample text:```…largest features in the 150-ms amplitude spectrum correspond to a loss of spectral features previously attributed to hK (Rothschild et al., 1988; Dioumaev and Braiman, 1997a), and a gain of features previously attributed to hL (Rothschild et al., 1988; Walter and Braiman, 1994; Chon et al.,…```
Sample intent: method



Sample text:```5 concentrations were computed for each participant using a hierarchical spatiotemporal model fit with a pragmatic estimation procedure described elsewhere [30,31].```
Sample intent: background



Sample text:```Pupillometry has been proposed as a simple and sensitive tool to detect subclinical autonomic dysfunction [30,31].```
Sample intent: background



Sample text:```The present observations support and extend earlier contentions that Parkinson patients prefer to adopt a closedloop control mode, adjusting their movements continuously on the basis of available visual information (Flowers 1976).```
Sample intent: result



Sample text:```…(LING)] thalamus (THA), as well as limbic/paralimbic regions [e.g. insula, superior temporal pole and inferior orbitofrontal cortex] (Table 2), which is in accordance with previous findings on functional brain networks constructed using resting-state fMRI (Achard et al., 2006; He et al., 2009b).```
Sample intent: result