An study on re-identification in RGB-D imagery

[EN]Re-identi fication is commonly accomplished using appearance features based on salient points and color information. In this paper, we make an study on the use of di fferent features exclusively obtained from depth images captured with RGB-D cameras. The results achieved, using simple geometric features extracted in a top-view setup, seem to provide useful descriptors for the re-identi fication task.

Commentary on "Timbre as an Elusive Component of Imagery for Music" by Freya Bailes

The study of musical timbre by Bailes (2007) raises important questions concerning the relative ease of imaging complex perceptual attributes such as timbre, compared to more unidimensional attributes. I also raise the issue of individual differences in auditory imagery ability, especially for timbre.

Effect of unilateral temporal-lobe excision on perception and imagery of songs

Auditory imagery for songs was studied in two groups of patients with left or right temporal-lobe excision for control of epilepsy, and a group of matched normal control subjects. Two tasks were used. In the perceptual task, subjects saw the text of a familiar song and simultaneously heard it sung. On each trial they judged if the second of two capitalized lyrics was higher or lower in pitch than the first. The imagery task was identical in all respects except that no song was presented, so that subjects had to generate an auditory image of the song. The results indicated that all subjects found the imagery task more difficult than the perceptual task, but patients with right temporal-lobe damage performed significantly worse on both tasks than either patients with left temporal-lobe lesions or normal control subjects. These results support the idea that imagery arises from activation of a neural substrate shared with perceptual mechanisms, and provides evidence for a right temporal- lobe specialization for this type of auditory imaginal processing.

Auditory Imagery and the Poor-Pitch Singer

The vocal imitation of pitch by singing requires one to plan laryngeal movements on the basis of anticipated target pitch events. This process may rely on auditory imagery, which has been shown to activate motor planning areas. As such, we hypothesized that poor-pitch singing, although not typically associated with deficient pitch perception, may be associated with deficient auditory imagery. Participants vocally imitated simple pitch sequences by singing, discriminated pitch pairs on the basis of pitch height, and completed an auditory imagery self-report questionnaire (the Bucknell Auditory Imagery Scale). The percentage of trials participants sung in tune correlated significantly with self-reports of vividness for auditory imagery, although not with the ability to control auditory imagery. Pitch discrimination was not predicted by auditory imagery scores. The results thus support a link between auditory imagery and vocal imitation.

Radical Verses: Aku Päiviö's Literary Influence on the Finnish Working-Class

Aku Päiviö was one of the most influential voices of the Finnish labor movement in North America—a poet who also wrote plays and novels, and an editor who worked for a variety of newspapers across the United States and Canada. During the height of the Finnish socialist movement from around 1904-1916, Päiviö published a number of poems that identified with the actions and ideologies of the working-class. He also edited for newspapers such as Kansan Lehti and Raivaaja, further extending his literary reach. Despite his prodigious publications and influence, however, little of Päiviö’s writing has been translated into English. This paper celebrates Päiviö’s legacy with some English translations of his poems, specifically those commemorating the 1913-14 Michigan Copper Strike, and illuminates how various thematic and structural relationships in these poems relate to the ideologies and movements of the time.

Probabilistic approach to cloud and snow detection on Advanced Very High Resolution Radiometer (AVHRR) imagery

Derivation of probability estimates complementary to geophysical data sets has gained special attention over the last years. Information about a confidence level of provided physical quantities is required to construct an error budget of higher-level products and to correctly interpret final results of a particular analysis. Regarding the generation of products based on satellite data a common input consists of a cloud mask which allows discrimination between surface and cloud signals. Further the surface information is divided between snow and snow-free components. At any step of this discrimination process a misclassification in a cloud/snow mask propagates to higher-level products and may alter their usability. Within this scope a novel probabilistic cloud mask (PCM) algorithm suited for the 1 km × 1 km Advanced Very High Resolution Radiometer (AVHRR) data is proposed which provides three types of probability estimates between: cloudy/clear-sky, cloudy/snow and clear-sky/snow conditions. As opposed to the majority of available techniques which are usually based on the decision-tree approach in the PCM algorithm all spectral, angular and ancillary information is used in a single step to retrieve probability estimates from the precomputed look-up tables (LUTs). Moreover, the issue of derivation of a single threshold value for a spectral test was overcome by the concept of multidimensional information space which is divided into small bins by an extensive set of intervals. The discrimination between snow and ice clouds and detection of broken, thin clouds was enhanced by means of the invariant coordinate system (ICS) transformation. The study area covers a wide range of environmental conditions spanning from Iceland through central Europe to northern parts of Africa which exhibit diverse difficulties for cloud/snow masking algorithms. The retrieved PCM cloud classification was compared to the Polar Platform System (PPS) version 2012 and Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 cloud masks, SYNOP (surface synoptic observations) weather reports, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical feature mask version 3 and to MODIS collection 5 snow mask. The outcomes of conducted analyses proved fine detection skills of the PCM method with results comparable to or better than the reference PPS algorithm.

Multi-Decadal Record of Ice Dynamics on Daugaard Jensen Gletscher, East Greenland, from Satellite Imagery and Terrestrial Measurements

The history of ice velocity and calving front position of Daugaard Jensen Gletscher, a large outlet glacier in East Greenland, is reconstructed from field measurements, aerial photography and satellite imagery for the period 1950-2001. The calving terminus of the glacier has remained in approximately the same position over the past similar to 50 years. There is no evidence of a change in ice motion between 1968 and 2001, based on a comparison of velocities derived from terrestrial surveying and feature tracking using sequential satellite images. Estimates of flux near the entrance to the fjord vs snow accumulation in the interior catchment show that Daugaard Jensen Gletscher has a small negative mass balance. This result is consistent with other mass-balance estimates for the inland region of the glacier.

Daytime Low Stratiform Cloud Detection on AVHRR Imagery

The near-real time retrieval of low stratiform cloud (LSC) coverage is of vital interest for such disciplines as meteorology, transport safety, economy and air quality. Within this scope, a novel methodology is proposed which provides the LSC occurrence probability estimates for a satellite scene. The algorithm is suited for the 1 × 1 km Advanced Very High Resolution Radiometer (AVHRR) data and was trained and validated against collocated SYNOP observations. Utilisation of these two combined data sources requires a formulation of constraints in order to discriminate cases where the LSC is overlaid by higher clouds. The LSC classification process is based on six features which are first converted to the integer form by step functions and combined by means of bitwise operations. Consequently, a set of values reflecting a unique combination of those features is derived which is further employed to extract the LSC occurrence probability estimates from the precomputed look-up vectors (LUV). Although the validation analyses confirmed good performance of the algorithm, some inevitable misclassification with other optically thick clouds were reported. Moreover, the comparison against Polar Platform System (PPS) cloud-type product revealed superior classification accuracy. From the temporal perspective, the acquired results reported a presence of diurnal and annual LSC probability cycles over Europe.