CSQUiD: an index and non-probability framework for constrained skyline query processing over uncertain data.

Uncertainty of data, the degree to which data are inaccurate, imprecise, untrusted, and undetermined, is inherent in many contemporary database applications, and numerous research endeavours have been devoted to efficiently answer skyline queries over uncertain data. The literature discussed two different methods that could be used to handle the data uncertainty in which objects having continuous range values. The first method employs a probability-based approach, while the second assumes that the uncertain values are represented by their median values.

Investigation of age-related facial variation among Angelman syndrome patients.

Angelman syndrome (AS) is one of the common genetic disorders that could emerge either from a 15q11-q13 deletion or paternal uniparental disomy (UPD) or imprinting or UBE3A mutations. AS comes with various behavioral and phenotypic variability, but the acquisition of subjects for experiment and automating the landmarking process to characterize facial morphology for Angelman syndrome variation investigation are common challenges. By automatically detecting and annotating subject faces, we collected 83 landmarks and 10 anthropometric linear distances were measured from 17 selected anatomical landmarks to account for shape variability.

A novel investigation of the effect of iterations in sliding semi-landmarks for 3D human facial images.

Background: Landmark-based approaches of two- or three-dimensional coordinates are the most widely used in geometric morphometrics (GM). As human face hosts the organs that act as the central interface for identification, more landmarks are needed to characterize biological shape variation. Because the use of few anatomical landmarks may not be sufficient for variability of some biological patterns and form, sliding semi-landmarks are required to quantify complex shape.

Morphometric approach to 3D soft-tissue craniofacial analysis and classification of ethnicity, sex, and age.

Background: The application of three-dimensional scan models offers a useful resource for studying craniofacial variation. The complex mathematical analysis for facial point acquisition in three-dimensional models has made many craniofacial assessments laborious.

Method: This study investigates three-dimensional (3D) soft-tissue craniofacial variation, with relation to ethnicity, sex and age variables in British and Irish white Europeans.

Landmark-based homologous multi-point warping approach to 3D facial recognition using multiple datasets.

Over the years, neuroscientists and psychophysicists have been asking whether data acquisition for facial analysis should be performed holistically or with local feature analysis. This has led to various advanced methods of face recognition being proposed, and especially techniques using facial landmarks. The current facial landmark methods in 3D involve a mathematically complex and time-consuming workflow involving semi-landmark sliding tasks.

3-Dimensional facial expression recognition in human using multi-points warping.

Background: Expression in H-sapiens plays a remarkable role when it comes to social communication. The identification of this expression by human beings is relatively easy and accurate. However, achieving the same result in 3D by machine remains a challenge in computer vision.