Human Shape Research Articles

RETRACTED: Cross-camera multi-person tracking by leveraging fast graph mining algorithm

Abstract Multiple person tracking is a very useful task in intelligent video surveillance, which is hindered by many challenges such as the variations of illumination, the irregular changes of human shapes and the particle occlusions. To tackle these challenges, in this paper, we propose a new online learning tracking system to generate the complete trajectory for each tracking object. In detection stage, we build a classifier for each tracking object by online learning in order to provide more accurate detection results. Online learning could real-time update the classifier for an accurately tracking results in the future. In the tracklet generation stage, we apply the spatiotemporal constrain to generate a set of reliable tracklets. Finally, we propose a new Part-based matching method to get the correlation between different tracklets and apply linear programming and greedy algorithm to handle the data association problem to generate the complete trajectory for each tracking object. In particular, our approach is able to cast the multiple cameras tracking problem as a data association problem. The experiments on our proposed method demonstrate state-of-the-art performance in multiple person tracking.

STRUCTURAL COMPARISON OF PROKARYOTIC AND EUKARYOTIC FOLATE TRANSPORTERS BY COMPUTATIONAL APPROACH

Objective: In silico approach has particularly drawn attention in providing a realistic representation needed to understand the fundamental molecular structure of a transporter. The importance of folate metabolism and role in the internalization of antifolates in eukaryotes have been studied extensively, but the structural study of folate transporters in Homo sapiens (HFT), Plasmodium falciparum (PFT), and Streptococcus sp. (SFT) is still lacking. This study was conducted to study and compare the structures of prokaryotic and eukaryotic folate transporters. Methods: HFT, PFT, and SFT were queried using blast and sequences were retrieved using National Center for Biotechnology and Information (NCBI) databases. This was superseded by structural and functional prediction of transporters. The structure has been generated using Swiss model which was visualized using PyMol and validated by Procheck and ERRAT analysis along with the values of different secondary structures mapping to diverse sections of the Ramachandran plot. The structural and functional comparison was performed by PROSO, ProFunc, TM Score, Porewalker, TMHMM, and Protscale. Result: All the parameters for structural comparison suggest that H. sapiens folate transporter is 16.67% and 17.72% identical to Plasmodium and Streptococcus whereas Plasmodium is 21.59% identical to Streptococcus. The evaluation of transmembrane helices and hydrophobicity resulted in the presence of 1, 4, and 12 membrane-spanning segments with predicted US, UDUD, and UDS as pore shape in Plasmodium, Streptococcus, and humans. Conclusion: Such folate receptors are the main targets for the specific conveyance of antifolates. The differences found between these species may offer possibilities for the development of new drugs in future.

An Arab Chariot Monument at Umm al-Jimāl

ABSTRACTThis article deals with unpublished fragments of sculpture in basalt found at Umm al-Jimāl, a site of a ruined Nabataean-Roman to Byzantine settlement in northern Jordan, six kilometers south of the border with Syria. The sculptures are typical for the southern Syrian volcanic zone of the Hawrān. The site is located at the extreme southern outcrop of this area, today part of The Hashemite Kingdom of Jordan.The fragments are contemporary with a better-preserved corpus of similar sculptures investigated by the authors in the basalt desert of al-Ledjā, ancient Trachon(itis). At Umm al-Jimāl, an analogous chariot group driven by deities can be identified by a wheel block with traces of the tail hairs of animals in harness. The assembled figures in human shape with drapery are parallel to the Sahr al-Ledjā statuary. Taking all extant evidence into account, the authors propose recognizing the sculptural remnants from Umm al-Jimāl as testimony of a strongly Hellenistic-Romanized embellishment of a hitherto little-known Arab-Nabataean sanctuary dating to the first or second century AD. This shrine together with its sculptures had most probably been destroyed by the Palmyrenean Campaign in the later third century AD.

Computational anatomy and diffeomorphometry: A dynamical systems model of neuroanatomy in the soft condensed matter continuum.

The nonlinear systems models of computational anatomy that have emerged over the past several decades are a synthesis of three significant areas of computational science and biological modeling. First is the algebraic model of biological shape as a Riemannian orbit, a set of objects under diffeomorphic action. Second is the embedding of anatomical shapes into the soft condensed matter physics continuum via the extension of the Euler equations to geodesic, smooth flows with inverses, encoding divergence for the compressibility of atrophy and expansion of growth. Third, is making human shape and form a metrizable space via geodesic connections of coordinate systems. These three themes place our formalism into the modern data science world of personalized medicine supporting inference of high-dimensional anatomical phenotypes for studying neurodegeneration and neurodevelopment. The dynamical systems model of growth and atrophy that emerges is one which is organized in terms of forces, accelerations, velocities, and displacements, with the associated Hamiltonian momentum and the diffeomorphic flow acting as the state, and the smooth vector field the control. The forces that enter the model derive from external measurements through which the dynamical system must flow, and the internal potential energies of structures making up the soft condensed matter. We examine numerous examples on growth and atrophy. This article is categorized under: Analytical and Computational Methods > Computational Methods Laboratory Methods and Technologies > Imaging Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models.

Mapping genetic variants for cranial vault shape in humans.

The shape of the cranial vault, a region comprising interlocking flat bones surrounding the cerebral cortex, varies considerably in humans. Strongly influenced by brain size and shape, cranial vault morphology has both clinical and evolutionary relevance. However, little is known about the genetic basis of normal vault shape in humans. We performed a genome-wide association study (GWAS) on three vault measures (maximum cranial width [MCW], maximum cranial length [MCL], and cephalic index [CI]) in a sample of 4419 healthy individuals of European ancestry. All measures were adjusted by sex, age, and body size, then tested for association with genetic variants spanning the genome. GWAS results for the two cohorts were combined via meta-analysis. Significant associations were observed at two loci: 15p11.2 (lead SNP rs2924767, p = 2.107 × 10−8) for MCW and 17q11.2 (lead SNP rs72841279, p = 5.29 × 10−9) for MCL. Additionally, 32 suggestive loci (p < 5x10-6) were observed. Several candidate genes were located in these loci, such as NLK, MEF2A, SOX9 and SOX11. Genome-wide linkage analysis of cranial vault shape in mice (N = 433) was performed to follow-up the associated candidate loci identified in the human GWAS. Two loci, 17q11.2 (c11.loc44 in mice) and 17q25.1 (c11.loc74 in mice), associated with cranial vault size in humans, were also linked with cranial vault size in mice (LOD scores: 3.37 and 3.79 respectively). These results provide further insight into genetic pathways and mechanisms underlying normal variation in human craniofacial morphology.

Photogrammetry: An accurate and cost-effective three-dimensional ice hockey helmet fit acquisition method

Ice hockey helmets must pass standardized impact tests to be certified for sale. However, these tests are performed with the helmet attached to a surrogate headform. Human head shapes are not uniform, and very few standards exist for helmet fitting for the common user. The goal of this study was to develop an accurate and cost-effective three-dimensional acquisition protocol to assess the geometric fit of human subject heads to a variety of ice hockey helmets. The study had three main objectives: First, a photogrammetry-based three-dimensional acquisition system was developed. Second, the researchers populated a database of both male human heads and ice hockey helmets by scanning five different helmet models from various manufacturers. Finally, the system accuracy and error were calculated using root mean squared errors between the dimensional difference curves of repeated scans. Errors were calculated by repeating the entire protocol error with 20 comparisons (root mean squared error = 2.83 mm), the alignment error with 5 comparisons (root mean squared error = 1.14 mm), and scaling error with 4 comparisons (root mean squared error = 1.84 mm). Suggestions are provided in the section “Discussion” on how to create a system that is more time efficient with higher resolution renders and lower error. A method that quantifies three-dimensional fit is the first step toward studying the relationship between helmet fit and user-specific helmet protection.

How Our Cognition Shapes and Is Shaped by Technology: A Common Framework for Understanding Human Tool-Use Interactions in the Past, Present, and Future.

Over the evolution, humans have constantly developed and improved their technologies. This evolution began with the use of physical tools, those tools that increase our sensorimotor abilities (e.g., first stone tools, modern knives, hammers, pencils). Although we still use some of these tools, we also employ in daily life more sophisticated tools for which we do not systematically understand the underlying physical principles (e.g., computers, cars). Current research is also turned toward the development of brain–computer interfaces directly linking our brain activity to machines (i.e., symbiotic tools). The ultimate goal of research on this topic is to identify the key cognitive processes involved in these different modes of interaction. As a primary step to fulfill this goal, we offer a first attempt at a common framework, based on the idea that humans shape technologies, which also shape us in return. The framework proposed is organized into three levels, describing how we interact when using physical (Past), sophisticated (Present), and symbiotic (Future) technologies. Here we emphasize the role played by technical reasoning and practical reasoning, two key cognitive processes that could nevertheless be progressively suppressed by the proficient use of sophisticated and symbiotic tools. We hope that this framework will provide a common ground for researchers interested in the cognitive basis of human tool-use interactions, from paleoanthropology to neuroergonomics.

Reporting Without Knowledge: the Absence of Human Rights in US Journalism Education

Journalists play an important role in the realization and protection of human rights worldwide, framing and shaping the public’s understanding of issues. In the United States, however, studies show that media coverage of human rights is inadequate and frequently inaccurate, with US journalists typically framing human rights as an exclusively international issue. This study helps to explain why this is the case through an examination of the human rights content of journalism education in the United States. Journalism education is dominated by undergraduate programs in the United States, yet data from this study show that human rights education is not part of journalism training programs at the undergraduate level (at the top 10 schools, ranked according to the number of graduates, there are no human rights courses for journalism majors) and is not a focus of most graduate-level training programs. Those schools that do teach human rights do so largely with a focus on events and violations abroad. The fact that journalists are not educated about international human rights law and standards or taught to view events through a human rights lens means that crucial opportunities are missed to frame topics as human rights issues, to inform the public, and to hold governments and other human rights violators accountable.

Magical Transformations on the Early Modern English Stage

Magical Transformations on the Early Modern English Stage

An entity based multi-direction cooperative deformation algorithm for generating personalized human shape

Personalized human shape plays an important role in system of virtual garment customization. In this paper, a new entity based multi-direction cooperative deformation algorithm (MDCD) is proposed to generate personalized human shape. We primarily extract the description parameters of entities using different direction sections based on unified division method. By introducing the entity curve interpolation and correspondence between elementary and target entities, the generated distortion of various human entities from simulated deformation function will be avoided. With the good capacity of accuracy and reusability of human entities, the MDCD algorithm can greatly improve the generation efficiency of personalized human shapes. The elementary entities on template model are firstly located using the division method of Poser, and description parameters on entities are then extracted based on the entity direction. Thus, shape characteristics can be represented by a set of direction curves on different angles by entity curve interpolation. Subsequently shape characteristics on personalized human body are generated by a comparison of direction curves of template and target entities. Finally, the MDCD algorithm is applied for generating personalized entities and shapes. Experiments show that compared with the existed algorithms, personalized human shapes generated by our method are smoother and more similar to the template model.

Single/Cross-Camera Multiple-Person Traffic Tracking by Graph Matching

Multiple person tracking is a very useful task in intelligent video surveillance, which is hindered by many challenges such as the variations of illumination, the irregular changes of human shapes and the particle occlusions. To tackle these challenges, in this paper, we propose a new online learning tracking system to generate the complete trajectory for each tracking object. In detection stage, we build a classifier for each tracking object by online learning in order to provide more accurate detection results. Online learning could real-time update the classifier for an accurately tracking results in the future. In the tracklet generation stage, we apply the spatiotemporal constrain to generate a set of reliable tracklets. Finally, we propose a new Part-based matching method to get the correlation between different tracklets and apply linear programming and greedy algorithm to handle the data association problem to generate the complete trajectory for each tracking object. In particular, our approach is able to cast the multiple cameras tracking problem as a data association problem. The experiments on our proposed method demonstrate state-of-the-art performance in multiple person tracking.

Authors in search of a character: ethnography and life writing

Not parallel but tangential: biography fits awkwardly with ethnography, doing well what ethnography does well to avoid. It cuts history to human shape, insinuates author into subject, reads cause in sequence, and turns the world into background. As ‘life writing’, biography rarely captures life: ethnography – immersed, immediate – does the job better. Participant observation opens up dimensions of behaviour and experience that the biographer, usually working second‐hand, can only dream of. Yet, as other papers in this collection argue, ethnography can benefit from a more concerted biographical approach. Without a grasp of character, history and circumstance, any account of human behaviour is stillborn. The constituents of meaning, the dynamic of emotions, and the unfolding of action are all biographical in shape and import. Without them we have only frames, scripts and abstract forces. The question is how far to mine the biographical seam. Does a mismatch between individuating narrative and self‐effacing folk theory disqualify? If the native disclaims a point of view, should the ethnographer construct one on his or her behalf? This paper considers the option in two contrasting Indonesian societies.

Correction: Investigating the case of human nose shape and climate adaptation.

[This corrects the article DOI: 10.1371/journal.pgen.1006616.].

El devenir-animal en “la pasión según G.H.” de Clarice Lispector (en lengua extranjera).

En &lt;em&gt;La pasión&lt;/em&gt; según G.H. de Clarice Lispector, después del contacto incierto con el cuerpo vivo de una cucaracha, la protagonista se adentra en una dimensión desconocida, que permanece al margen de las palabras y los nombres. El movimiento de desterritorialización, que inaugura el proceso del devenir-animal, establece una zona de intercambio entre el hombre y el animal, que posibilita el cuestonamiento crítco de los límites internos que circunscriben el estatuto del ser y la identdad, en contra de la (falsa) autocomplacencia que exhibe el sujeto cartesiano. De esta manera, gracias al contacto incierto con una alteridad irreductble, el sujeto pierde su envoltura humana y descubre la dimensión de lo neutro, que permite cuestonar la topología oposicional que estructura el binarismo sexual excluyente del sistema capitalista y hetero-patriarcal, con el fn de reclamar la multplicidad sexual que produce la diferencia. Así, en una especie de lengua extranjera, el trabajo de Lispector posibilita la inscripción de diferentes cuerpos sexuados en la escritura, en contra del monolingüismo que instaura el sistema falo-logocéntrico del mundo occidental.

Real-time based human-fall detection from an indoor video surveillance

In this paper, we present a human fall detection method from visual surveillance. In the first step, background subtraction is performed using improved GMM to find the foreground objects. In the second step, contour-based human template matching is applied to categorise the human or non-human object. It helps to detect fall incident by providing sudden change in generated score after matching. Height-width ratio and area of contour of an object is computed in the third step to decide whether the human shape is changed or not. In the fourth step, distance between top and mid centre of rectangle covering human is computed, if it is less than a certain threshold, then human fall is confirmed. Finally, if inactive pose of human is continued till 100 consecutive frames, then an alarm is generated to alert the people at home to provide treatment on time. Experiments have been performed on two different datasets having different usual and unusual fall incidents. Experimental results show that proposed system works well efficiently and effectively in real-time for recognising human fall.

Real-time based human-fall detection from an indoor video surveillance

In this paper, we present a human fall detection method from visual surveillance. In the first step, background subtraction is performed using improved GMM to find the foreground objects. In the second step, contour-based human template matching is applied to categorise the human or non-human object. It helps to detect fall incident by providing sudden change in generated score after matching. Height-width ratio and area of contour of an object is computed in the third step to decide whether the human shape is changed or not. In the fourth step, distance between top and mid centre of rectangle covering human is computed, if it is less than a certain threshold, then human fall is confirmed. Finally, if inactive pose of human is continued till 100 consecutive frames, then an alarm is generated to alert the people at home to provide treatment on time. Experiments have been performed on two different datasets having different usual and unusual fall incidents. Experimental results show that proposed system works well efficiently and effectively in real-time for recognising human fall.

Anthropometric study of the frontal sinus on plain radiographs in Delta State University Teaching Hospital

INTRODUCTION: The paranasal sinuses are air-filled spaces located within the bones of the skull and face. The different anatomical dimensions of paranasal sinuses can be obtained from plain radiograph and computed tomography images. Determining the possible significant variation of the right and frontal sinuses of males and females is essential for clinical purpose. PURPOSE OF THE STUDY: The purpose of this study, therefore, was to measure the anthropometric length and width of the frontal sinus on plain radiograph in different age groups and to determine the possible variations in males and females. MATERIALS AND METHODS: This descriptive cross-sectional study adopted the simple random sampling technique. The study population comprised 200 individuals (100 males and 100 females). RESULTS: Frontal sinus length and width were measured using the inelastic plastic ruler (in centimeter) and recorded on a data sheet pro forma. The mean total frontal sinus length and frontal sinus width across the entire population for both the right and left sides as regards males and females were given as (4.42 ± 4.79 cm, 3.85 ± 4.24 cm, 4.05 ± 4.44 cm, 3.57 ± 3.93 cm) and (3.64 ± 4.01 cm, 3.29 ± 3.46 cm, 3.23 ± 3.57 cm, 2.83 ± 3.13 cm), respectively. The Student's t-test statistics between the right and left sides in each of the studied parameters were highly statistically significant (P = 0.000). CONCLUSION: The frontal sinus is a constant structure in human beings, but shape and dimensions may vary among individuals; thus, the dimorphic nature of the left frontal sinus dimensions has implications for human identification.

A comparative study on human and domestic animal bitemark patterns: An aid in forensic investigation

Bitemark analysis of humans and domestic animals is by far the most demanding and complicated part of forensic dentistry. This study compared and analyzed the bite mark impression patterns of 34 domestic animals and 16 humans. Bitemark comparison included comparing the bitemark of the suspected biter's distinctive dental features to determine whether a link exists between the two sets of evidence. Oval or elliptical arch shape of humans, circular to oval shape of dog, circular arch shape of cat was noted. The incisor morphology for humans was rectangular shape, oval to rectangular for dogs, circular for cats was observed. The inter canine distance of humans measured on dental cast ranged from 22–40 mm with a standard deviation of 5.0 and mean of 33.2, 32–50 mm with a standard deviation of 4.11 and mean of 38.44 for dogs, 11.80 to 18.24 mm with a standard deviation of 2.44 and mean of 16.14 for cats. Intercanine distance, arch shape are few, simple reliable parameter to differentiate between bite marks that are produced by humans and domestic animals. The outcome of the study serves and helps the forensic fraternity of different expertise such as forensic odontologist, forensic pathologists, veterinarians, biologists, crime investigators, and others.

Detection of Human Falls on Furniture Using Scene Analysis Based on Deep Learning and Activity Characteristics

Automatic human fall detection is one important research topic in caring for vulnerable people, such as elders at home and patients in medical places. Over the past decade, numerous methods aiming at solving the problem were proposed. However, the existing methods only focus on detecting human themselves and cannot work effectively in complicated environments, especially for the falls on furniture. To alleviate this problem, a new method for human fall detection on furniture using scene analysis based on deep learning and activity characteristics is presented in this paper. The proposed method first performs scene analysis using a deep learning method faster R-CNN to detect human and furniture. Meanwhile, the space relation between human and furniture is detected. The activity characteristics of the detected people, such as human shape aspect ratio, centroid, motion speed are detected and tracked. Through measuring the changes of these characteristics and judging the relations between the people and furniture nearby, the falls on furniture can be effectively detected. Experiment results demonstrated that our approach not only accurately and effectively detected falls on furniture, such as sofa and chairs but also distinguished them from other fall-like activities, such as sitting or lying down, while the existing methods have difficulties to handle these. In our experiments, our algorithm achieved 94.44% precision, 94.95% recall, and 95.50% accuracy. The proposed method can be potentially used and integrated as a medical assistance in health care and medical places and appliances.

A fast Human detection algorithm for container reach stackers

With the development of automation in the ports, more and more attention has been paid to the effective real-time monitoring of personnel intrusion into the unmanned area in the process of operation. In this paper, a fast human detection algorithm is proposed. Firstly, by improving HOG algorithm flow, the speed of feature extraction of HOG is greatly accelerated. Then, based on the HOG features, a 2-stage classifier based on Adaboost is proposed, which trains the front/back and side of the human sample library, so that the algorithm can adapt to the multi-pose human shape detection under the complex ports backgrounds. Finally, this paper presented a group of experiments about human detection on the container reach stacker of Shanghai International Port(Group) YIDONG Container Terminal Branch. The results show that the recognition accuracy of the combined algorithm of fast HOG and 2-stage classifier can reach 95% , and the detection time can be within 150ms. It realizes the calculation of 5-channel video human detection at the same time in a small embedded board, and meets the security requirements of unmanned areas in the ports.