Automatic learning of gait signatures for people identification

This work targets people identification in video based on the way they walk (i.e. gait). While classical methods typically derive gait signatures from sequences of binary silhouettes, in this work we explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (i.e. optical flow components). We carry out a thorough experimental evaluation of the proposed CNN architecture on the challenging TUM-GAID dataset. The experimental results indicate that using spatio-temporal cuboids of optical flow as input data for CNN allows to obtain state-of-the-art results on the gait task with an image resolution eight times lower than the previously reported results (i.e. 80x60 pixels).Comment: Proof of concept paper. Technical report on the use of ConvNets (CNN) for gait recognition. Data and code: http://www.uco.es/~in1majim/research/cnngaitof.htm

Social influence and position effects

A wide range of personal choices rely on the opinions or ratings of other individuals. This information has recently become a convenient way of simplifying the decision process. For instance, in online purchases of products and services, the possible choices or alternatives are often characterized by their position in a certain presentation order (or list) and their popularity, derived from an aggregate signal of the behavior of others. We have performed a laboratory experiment to quantify and compare popularity (or social influence) and position effects in a stylized setting of homogeneous preferences, with a small number of alternatives but considerable time constraints. Our design allows for the distinction between two phases in the decision process: (1) how agents search (i.e., not only which alternatives are analyzed but also in which order) and (2) how they ultimately choose. We find that in this process there are significant popularity and position effects. Position effects are stronger than social influence effects for predicting the searching behavior, however, social influence determines to a larger extent the actual choice. The reason is that social influence generates a double effect; it directly affects the final choice (independently on what alternative has been searched more thoroughly) and indirectly alters choice through the searching behavior which, in turn, is also affected by popularity. A novelty of our approach is that we account for personal traits and provide an individual analysis of sensitivity to both social influence and position effects. Surprisingly, we find that overconfident individuals are more influenceable, whereas other personal characteristics (e.g., gender and risk aversion) do not play a significant role in this context

The XMM-Newton view of PG quasars: II. Properties of the Fe K-alpha line

The properties of the fluorescence Fe K-alpha emission lines of a sample of 38 quasars (QSOs) observed with XMM-Newton are studied. These objects are included in the optically selected sample from the Palomar-Green (PG) Bright Quasar Survey with an X-ray luminosity 1.3E43<L(2-10 keV)<5.1E45 ergs/s and z<1.72. For each object in the sample, we investigated the presence of both narrow and broad iron lines in detail. A total of 20 out of the 38 QSOs show evidence of an Fe K-alpha emission line with a narrow profile. The majority of the lines are consistent with an origin in low ionization material, which is likely to be located in the outer parts of the accretion disk, the molecular torus, and/or the Broad Line Region. The average properties of the narrow Fe K-alpha emission line observed in the sample are similar to those of Seyfert type galaxies as inferred from recent XMM-Newton and Chandra studies. A broad line has been significantly detected in only three objects. Furthermore, we studied the relationship between the equivalent width (EW) of the iron line and the hard band X-ray luminosity for radio quiet quasars. The analysis indicates that no clear correlation between the strength of the line and the hard X-ray luminosity is present, and our results do not show compelling evidence for an anticorrelation between these two quantities, i.e. the so-called X-ray Baldwin effect.Comment: 10 pages, 3 figures, accepted by A&

A long hard look at the minimum state of PG 2112+059 with XMM-Newton

XMM-Newton successfully detected the minimum state of PG 2112+059 during a short snapshot observation and performed a long follow-up observation. The high signal-to-noise spectra are modelled assuming different emission scenarios and compared with archival spectra taken by XMM-Newton and Chandra. The PG 2112+059 X-ray spectra acquired in May 2007 allowed the detection of a weak iron fluorescent line, which is interpreted as being caused by reflection from neutral material at some distance from the primary X-ray emitting source. The X-ray spectra of PG 2112+059 taken at five different epochs during different flux states can be interpreted within two different scenarios. The first consists of two layers of ionised material with column densities of N_H ~5 x 10^22 cm^-2 and N_H ~3.5 x 10^23 cm^-2, respectively. The first layer is moderately ionised and its ionisation levels follow the flux changes, while the other layer is highly ionised and does not show any correlation with the flux of the source. The spectra can also be interpreted assuming reflection by an ionised accretion disk seen behind a warm absorber. The warm absorber ionisation is consistent with being correlated with the flux of the source, which provides an additional degree of self-consistency with the overall reflection-based model. We explain the spectral variability with light bending according to the models of Miniutti and Fabian and constrain the black hole spin to be a/M > 0.86. Both scenarios also assume that a distant cold reflector is responsible for the Fe K \alpha emission line. Light bending provides an attractive explanation of the different states of PG 2112+059 and may also describe the physical cause of the observed properties of other X-ray weak quasars.Comment: 15 pages, 12 figures, A&A latex, accepted for publication in Astronomy & Astrophysic

Utilizing Colored Dissolved Organic Matter to Derive Dissolved Black Carbon Export by Arctic Rivers

Wildfires have produced black carbon (BC) since land plants emerged. Condensed aromatic compounds, a form of BC, have accumulated to become a major component of the soil carbon pool. Condensed aromatics leach from soils into rivers, where they are termed dissolved black carbon (DBC). The transport of DBC by rivers to the sea is a major term in the global carbon and BC cycles. To estimate Arctic river DBC export, 25 samples collected from the six largest Arctic rivers (Kolyma, Lena, Mackenzie, Ob’, Yenisey and Yukon) were analyzed for dissolved organic carbon (DOC), colored dissolved organic matter (CDOM), and DBC. A simple, linear regression between DOC and DBC indicated that DBC accounted for 8.9 ± 0.3% DOC exported by Arctic rivers. To improve upon this estimate, an optical proxy for DBC was developed based upon the linear correlation between DBC concentrations and CDOM light absorption coefficients at 254 nm (a254). Relatively easy to measure a254 values were determined for 410 Arctic river samples between 2004 and 2010. Each of these a254 values was converted to a DBC concentration based upon the linear correlation, providing an extended record of DBC concentration. The extended DBC record was coupled with daily discharge data from the six rivers to estimate riverine DBC loads using the LOADEST modeling program. The six rivers studied cover 53% of the pan-Arctic watershed and exported 1.5 ± 0.1 million tons of DBC per year. Scaling up to the full area of the pan-Arctic watershed, we estimate that Arctic rivers carry 2.8 ± 0.3 million tons of DBC from land to the Arctic Ocean each year. This equates to ~8% of Arctic river DOC export, slightly less than indicated by the simpler DBC vs DOC correlation-based estimate. Riverine discharge is predicted to increase in a warmer Arctic. DBC export was positively correlated with river runoff, suggesting that the export of soil BC to the Arctic Ocean is likely to increase as the Arctic warms

Resonant Scattering and Recombination in CAL 87

The eclipsing supersoft X-ray binary CAL 87 has been observed with Chandra on August 13/14, 2001 for nearly 100 ksec, covering two full orbital cycles and three eclipses. The shape of the eclipse light curve derived from the zeroth-order photons indicates that the size of the X-ray emission region is about 1.5 solar radii. The ACIS/LETG spectrum is completely dominated by emission lines without any noticeable continuum. The brightest emission lines are significantly redshifted and double-peaked, suggestive of emanating in a 2000 km/s wind. We model the X-ray spectrum by a mixture of recombination and resonant scattering. This allows us to deduce the temperature and luminosity of the ionizing source to be kT = 50-100 eV and L_X = 5E37 erg/s.Comment: To appear in Proceedings of IAU Coll. 194 "Compact binaries in the Galaxy and beyond" (Rev. Mex. A&A Conf. Series), eds. G. Tovmassian and E. Sio

A RELATIONAL STUDY OF SELF-TAUGHT AND FORMALLY TRAINED MUSICIANS: TRENDS WITHIN MEMORY AND SOCIOECONOMIC FACTORS

It has been well documented that musicians perform better in memory tasks than non-musicians. The current study utilized self-taught musicians, formally trained musicians, and non-musicians, and focused on short-term memory (STM), musicianship, and SES factors to explore this finding. Do the memory benefits of musical training extend to self-taught musicians? First, we addressed musicianship amongst all groups using the Goldsmith’s Musical Sophistication Index (GMSI), which contained subjective and objective measures. The subjective measure was a survey regarding the role of music in daily life. In the objective measures, participants completed tests of beat and melody perception. To measure STM, participants completed an audio-only and audiovisual serial recall task. A correlational analysis was run to view relationships among the five subjective measures with one another and with the GMSI general score. Another correlational analysis was run between the general score and objective tasks. Performance on the recall tasks was examined among all groups. Lastly, recall scores and objective measures were tested for any correlations. Through a regression analysis, memory was predicted by musical training, and further analysis showed a difference in memory scores between musician groups. However, no differences were found in SES or aptitude between musician types, as they were not significant predictors. The significant difference in our memory variable indicates that there could be important differences in the two methods of learning music, and this finding could have broader implications for communities and individuals without the means of learning through school or private lessons. However, further research is warranted before firm conclusions can be drawn