A topological approach for segmenting human body shape

Segmentation of a 3D human body, is a very challenging problem in applications exploiting human scan data. To tackle this problem, the paper proposes a topological approach based on the discrete Reeb graph (DRG) which is an extension of the classical Reeb graph to handle unorganized clouds of 3D points. The essence of the approach concerns detecting critical nodes in the DRG, thereby permitting the extraction of branches that represent parts of the body. Because the human body shape representation is built upon global topological features that are preserved so long as the whole structure of the human body does not change, our approach is quite robust against noise, holes, irregular sampling, frame change and posture variation. Experimental results performed on real scan data demonstrate the validity of our method

A Survey on Ear Biometrics

Recognizing people by their ear has recently received significant attention in the literature. Several reasons account for this trend: first, ear recognition does not suffer from some problems associated with other non contact biometrics, such as face recognition; second, it is the most promising candidate for combination with the face in the context of multi-pose face recognition; and third, the ear can be used for human recognition in surveillance videos where the face may be occluded completely or in part. Further, the ear appears to degrade little with age. Even though, current ear detection and recognition systems have reached a certain level of maturity, their success is limited to controlled indoor conditions. In addition to variation in illumination, other open research problems include hair occlusion; earprint forensics; ear symmetry; ear classification; and ear individuality. This paper provides a detailed survey of research conducted in ear detection and recognition. It provides an up-to-date review of the existing literature revealing the current state-of-art for not only those who are working in this area but also for those who might exploit this new approach. Furthermore, it offers insights into some unsolved ear recognition problems as well as ear databases available for researchers

3D Face tracking and gaze estimation using a monocular camera

Estimating a user’s gaze direction, one of the main novel user interaction technologies, will eventually be used for numerous applications where current methods are becoming less effective. In this paper, a new method is presented for estimating the gaze direction using Canonical Correlation Analysis (CCA), which finds a linear relationship between two datasets defining the face pose and the corresponding facial appearance changes. Afterwards, iris tracking is performed by blob detection using a 4-connected component labeling algorithm. Finally, a gaze vector is calculated based on gathered eye properties. Results obtained from datasets and real-time input confirm the robustness of this metho

A discrete Reeb graph approach for the segmentation of human body scans

Segmentation of 3D human body (HB) scan is a very challenging problem in applications exploiting human scan data. To tackle this problem, we propose a topological approach based on discrete Reeb graph (DRG) which is an extension of the classical Reeb graph to unorganized cloud of 3D points. The essence of the approach is detecting critical nodes in the DRG thus permitting the extraction of branches that represent the body parts. Because the human body shape representation is built upon global topological features that are preserved so long as the whole structure of the human body does not change, our approach is quite robust against noise, holes, irregular sampling, moderate reference change and posture variation. Experimental results performed on real scan data demonstrate the validity of our method

Form-function relationships in dragonfly mandibles under an evolutionary perspective

© 2017 The Author(s). Functional requirements may constrain phenotypic diversification or foster it. For insect mouthparts, the quantification of the relationship between shape and function in an evolutionary framework remained largely unexplored. Here, the question of a functional influence on phenotypic diversification for dragonfly mandibles is assessed with a large-scale biomechanical analysis covering nearly all anisopteran families, using finite element analysis in combination with geometric morphometrics. A constraining effect of phylogeny could be found for shape, the mandibular mechanical advantage (MA), and certain mechanical joint parameters, while stresses and strains, the majority of joint parameters and size are influenced by shared ancestry. Furthermore, joint mechanics are correlated with neither strain nor mandibular MA and size effects have virtually play no role for shape or mechanical variation. The presence of mandibular strengthening ridges shows no phylogenetic signal except for one ridge peculiar to Libelluloidea, and ridge presence is also not correlated with each other. The results suggest that functional traits are more variable at this taxonomic level and that they are not influenced by shared ancestry. At the same time, the results contradict the widespread idea that mandibular morphology mainly reflects functional demands at least at this taxonomic level. The varying functional factors rather lead to the same mandibular performance as expressed by the MA, which suggests a many-to-one mapping of the investigated parameters onto the same narrow mandibular performance space