Holistic Image Research Articles

Action recognition from mutually incoherent pose bases in static image

Action recognition in static image is challenging. The authors propose mutually incoherent pose bases which are implicit poselet co-occurrences and are learned by dictionary training to describe body pose. Poselets in a pose basis are not constrained in space and quantity, thus pose basis can describe body pose more flexibly than k-poselet. In their method, body pose in an image is represented by a sparse linear combination of pose bases because pose in an action varies while each image only captures a snapshot from a single viewpoint. In dictionary training, the challenge is how to stabilise the sparse representation which is the input of Support Vector Machine (SVM) for action recognition, because the original pose signal is ambiguous while dictionary is an over complete matrix. Their solution is to add cumulative coherence as penalty in objective function and induce pose bases become mutually incoherent. They evaluate the method on two popular datasets and experiment results show the pose representation has encouraging performance in action recognition. Furthermore, they empirically exploit the complementary role of the local pose feature with deep convolutional neural network features from holistic image. Experiment results demonstrate aggressive performance improvement by concatenating the two features.

Perceptual uniform descriptor and ranking on manifold for image retrieval

Incompatibility of image descriptor and ranking has been often neglected in image retrieval. In this paper, Manifold Learning and Gestalt Psychology Theory are involved to solve the problem of incompatibility. A new holistic descriptor called Perceptual Uniform Descriptor (PUD) based on Gestalt psychology is proposed, which combines color and gradient direction to imitate human visual uniformity. PUD features in the same class images distributes on one manifold in most cases, as PUD improves the visual uniformity of the traditional descriptors. Thus, we use manifold ranking and PUD to realize image retrieval. Experiments were carried out on four benchmark data sets, and the proposed method is shown to greatly improve the accuracy of image retrieval. Our experimental results in Ukbench and Corel-1K datasets demonstrate that N-S score reached 3.58 (HSV 3.4) and mAP at 81.77% (ODBTC 77.9%) respectively by utilizing PUD which has only 280 dimensions. The results are higher than other holistic image descriptors including local ones as well as state-of-the-arts retrieval methods.

New non‐negative sparse feature learning approach for content‐based image retrieval

One key issue in content-based image retrieval is to extract effective features so as to represent the visual content of an image. In this study, a new non-negative sparse feature learning approach to produce a holistic image representation based on low-level local features is presented. Specifically, a modified spectral clustering method is introduced to learn a non-negative visual dictionary from local features of training images. A non-negative sparse feature encoding method termed non-negative locality-constrained linear coding (NNLLC) is proposed to improve the popular locality-constrained linear coding method so as to obtain more meaningful and interpretable sparse codes for feature representation. Moreover, a new feature pooling strategy named kMaxSum pooling is proposed to alleviate the information loss of the sum pooling or max pooling strategy, which produces a more effective holistic image representation and can be viewed as a generalisation of the sum and max pooling strategies. The retrieval results carried out on two public image databases demonstrate the effectiveness of the proposed approach.

FUNDAMENTALIZATION OF HIGHER PROFESSIONAL EDUCATION OF FUTURE SOCIAL WORKERS: ANTHROPOLOGICAL AND HUMANISTIC APPROACHES

The ideological basis of fundamentalization of higher professional education of future social workers from the position of education in «breadth» are analysed in the article. It is found out that unlike the fundamentalization of the education in «depth», which promotes a more enhanced training of future specialists in predetermined subjects, education in «breadth» provides conditions for the complete development of future specialist. Based on a synthesis it is proved that the fundamentality of studentsʼ knowledge is formed in a uninterrupted, parity interaction with teachers in the classroom and extracurricular, vitacultural space. Thus fundamentalization of professional training synthesizes the future social workersʼ knowledge that is characterized by interdisciplinarity, versatility and complicity. As a result obtained education of experts is directed to overcome fragmented consciousness and intelligence.The scientific thought about impossibility of efficiency of fundamentalization of higher education of future social workers without its antropologization and humanization is formed. In-depth knowledge about man as an object of future professional activity contributes to the development of system thinking in students, their professional identity, the ability to see every man his uniqueness, originality, exclusivity.Social workers are working in the system «man – man», so meaningfully disclosed, that concept «love to the human» is described and defined not only with basic knowledge and skills of the future professionals, but also values, motivation activities, style of relationships with people, personal culture, ability to develop creative potential. That is why fundamentalization of professional training of young people in the higher educational institution successfully combines the functions of education, training and self-development of personality of students, contributes to the quality of their training at the university, develops the responsibility for their attitude to humanity and the planet for the results of their own activities.It is argumented that anthropological and humanistic approaches contribute to a more thorough explanation and understanding of fundamentalization of education in institution of higher education. They emphasize the importance of recreation in the content of education holistic image of man as a biopsychosocial system and active and creative possibilities of the student with his desire to realize himself on the principles of love to the human in the public interest.According to the results of the research, it is found out that implementation of these approaches to fundamentalization of higher professional education improves the quality of training of future social workers at the higher educational institution in case of implementing leading anthropological and humanistic ideas in theoretical subjects and effectivepractices in social units.

What really happens in Kavos

PurposeThe purpose of this study is to compare and contrast the organic destination image of Kavos, as portrayed through irresponsible tourism-related behaviours on “reality” TV programmes, with its complex image according to members of the local community.Design/methodology/approachA thematic analysis was undertaken of four reality television programmes. This was compared with the qualitative data gathered from depth interviews.FindingsThe portrayal of tourism in Kavos focuses on only one narrow segment of young British high-season tourists. Thus, the destination image is unbalanced, neglects changing patterns of tourism throughout the year and neglects various other stakeholders in the destination’s image formation process.Research limitations/implicationsA limitation of this study is that it explored reality television programmes that focused on Kavos and featured a younger demographic. Further studies could look to include a range of reality programmes from different geographic locations and, include other demographics.Practical implicationsA more holistic image, created and communicated by those responsible for managing the destination, could go some way to ameliorating the disparities between what is portrayed on reality television and what really happens in the resort.Social implicationsMost media portrayal about Kavos focuses only on irresponsible tourist behaviours. This paper explores the physical and social aspects of place-making, an approach that thus becomes more inclusive of considering a place from the perspective of both its permanent and transient inhabitants.Originality/valueBy including in the authors’ data sources the under-researched phenomenon of reality television programmes, along with insights gained from members of the local community, this study makes a number of contributions to: the way destinations are theorised and conceptualised; and to the way tourism destinations with negative images may be approached both theoretically and in practice.

Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition.

Human faces in surveillance videos often suffer from severe image blur, dramatic pose variations, and occlusion. In this paper, we propose a comprehensive framework based on Convolutional Neural Networks (CNN) to overcome challenges in video-based face recognition (VFR). First, to learn blur-robust face representations, we artificially blur training data composed of clear still images to account for a shortfall in real-world video training data. Using training data composed of both still images and artificially blurred data, CNN is encouraged to learn blur-insensitive features automatically. Second, to enhance robustness of CNN features to pose variations and occlusion, we propose a Trunk-Branch Ensemble CNN model (TBE-CNN), which extracts complementary information from holistic face images and patches cropped around facial components. TBE-CNN is an end-to-end model that extracts features efficiently by sharing the low- and middle-level convolutional layers between the trunk and branch networks. Third, to further promote the discriminative power of the representations learnt by TBE-CNN, we propose an improved triplet loss function. Systematic experiments justify the effectiveness of the proposed techniques. Most impressively, TBE-CNN achieves state-of-the-art performance on three popular video face databases: PaSC, COX Face, and YouTube Faces. With the proposed techniques, we also obtain the first place in the BTAS 2016 Video Person Recognition Evaluation.

Holistically-Nested Edge Detection

We develop a new edge detection algorithm that addresses two important issues in this long-standing vision problem: (1) holistic image training and prediction; and (2) multi-scale and multi-level feature learning. Our proposed method, holistically-nested edge detection (HED), performs image-to-image prediction by means of a deep learning model that leverages fully convolutional neural networks and deeply-supervised nets. HED automatically learns rich hierarchical representations (guided by deep supervision on side responses) that are important in order to resolve the challenging ambiguity in edge and object boundary detection. We significantly advance the state-of-the-art on the BSDS500 dataset (ODS F-score of 0.790) and the NYU Depth dataset (ODS F-score of 0.746), and do so with an improved speed (0.4 s per image) that is orders of magnitude faster than some CNN-based edge detection algorithms developed before HED. We also observe encouraging results on other boundary detection benchmark datasets such as Multicue and PASCAL-Context.

Diffusion tensor imaging of the visual pathway in glaucomatous optic nerve atrophy

In Germany more than one million inhabitants suffer from glaucoma, more than 100,000 are threatened with blindness because glaucoma is often diagnosed too late or not at all. Diagnosis and monitoring is usually carried out "only" by examination of the retina and not the whole visual pathway. However, the eye is just "the tip of the iceberg" of the actual visual pathway, which extends through the brain to the visual cortex. The interdisciplinary holistic assessment of the whole visual pathway in glaucoma is of crucial importance because glaucoma is a complex neurodegenerative disease. Subtypes, such as normal tension glaucoma (NTG), seem to originate from primary damage to the intracranial visual pathway with secondary retrograde retinal degeneration. Recent studies including glaucoma patients and healthy controls could show that diffusion tensor imaging with calculation of diffusion coefficients, i.e. fractional anisotropy (FA), mean and radial diffusivity (MD and RD) as markers of axonal integrity, provide the potential to assess the intracranial visual pathway with a high correlation to established ophthalmological examinations. In particular, calculation of FA maps of the visual pathway and accompanying voxel-based approaches, can be integrated into clinical routine. Thus, detection of glaucoma-related intracranial alterations, even in early stages of the disease, as well as differentiation of different glaucoma subtypes, is made possible. Furthermore, the diagnosis of normal tension glaucoma seems to be possible much earlier with these new imaging techniques compared to established ophthalmological work-up. Moreover, holistic imaging provides new insights into the pathophysiology of this form of glaucoma. This review article gives an overview of these novel magnetic resonance imaging techniques for assessment of the visual pathway in glaucomatous optic nerve atrophy and reveals the potential of an interdisciplinary approach.

Unsupervised Learning of Multi-Level Descriptors for Person Re-Identification

In this paper, we propose a novel coding method named weighted linear coding (WLC) to learn multi-level (e.g., pixel-level, patch-level and image-level) descriptors from raw pixel data in an unsupervised manner. It guarantees the property of saliency with a similarity constraint. The resulting multi-level descriptors have a good balance between the robustness and distinctiveness. Based on WLC, all data from the same region can be jointly encoded. Consequently, when we extract the holistic image features, it is able to preserve the spatial consistency. Furthermore, we apply PCA to these features and compact person representations are then achieved. During the stage of matching persons, we exploit the complementary information resided in multi-level descriptors via a score-level fusion strategy. Experiments on the challenging person re-identification datasets - VIPeR and CUHK 01, demonstrate the effectiveness of our method.

Superpixel-Based Face Sketch–Photo Synthesis

Face sketch–photo synthesis technique has attracted growing attention in many computer vision applications, such as law enforcement and digital entertainment. Existing methods either simply perform the face sketch–photo synthesis on the holistic image or divide the face image into regular rectangular patches ignoring the inherent structure of the face image. In view of such situations, this paper presents a novel superpixel-based face sketch–photo synthesis method by estimating the face structures through image segmentation. In our proposed method, face images are first segmented into superpixels, which are then dilated to enhance the compatibility of neighboring superpixels. Each input face image induces a specific graphical structure modeled by Markov networks. We employ a two-stage synthesis process to learn the face structures through Markov networks constructed from two scales of dilation, respectively. Experiments on several public databases demonstrate that our proposed face sketch–photo synthesis method achieves superior performance compared with the state-of-the-art methods.

On stratification in changing higher education: the “analysis of status” revisited

This article seeks to shed light on current dynamics of stratification in changing higher education and proposes an analytical perspective to account for these dynamics based on Martin Trow’s work on “the analysis of status.” In research on higher education, the term “stratification” is generally understood as a metaphor that describes a stable vertical order. In sectors that are experiencing considerable change, such an order is still in the making. In following Trow, we propose to look at stratification as an open ordering process that constructs verticality. We distinguish between sector and field stratification, i.e., between stratification through coercive regulation by the state and through status judgements by a wide range of stakeholders. Within the last decade, field stratification has grown in importance as governments in continental Europe have provided universities with more leeway. Specific devices (rankings, etc.) channel such judgements and construct images of how a field appears. By applying this concept to two empirical cases from German higher education, we will show how devices redefine verticality in higher education through specific field images. First, master rankings in business administration/economics expand the topological boundaries to include degree programs outside national sectors, raise the importance of alumni and increase the recruitment of female students. Second, the Excellence Initiative triggers the construction of a new unregulated sector of doctoral education; excellent graduate schools model themselves along the scales of the field image as selective, interdisciplinary, international, and part of a holistic university image.

Assessment the Level Sustainability of Rural Destinations to Achieve Rural Tourism Development with Destination Image Modifier (Case Study: Derak Dehestan- Shiraz County)

Extended abstract 1. INTRODUCTION Rural tourism can be defined as the ‘country experience’ which encompasses a wide range of attractions and activities that take place in agricultural or non-urban areas. Its essential characteristics include wide-open spaces, low levels of tourism development, and opportunities for visitors to directly experience agricultural and/or natural environments. In the recent years, aside from its positive economic and social influences in the rural areas, tourism has been strongly accorded as a resource for the renewal and sustainable development of these areas. In fact, rural tourism is considered as a means of sustainable Development and natural resources protection. On the other hand, rural destination image is connected to common representations of rurality in tourism and rural imaginaries. In Iran, 30 percent of the population live in rural areas. The villages of Drak Dehestan in Fars province is one of the most important region in Iran that has the potential for tourism sustainable development. In this way, the purpose of this paper is assessing the economic, social and environmental sustainability with regard to destination image role as a modifier factor in villages of Derak Dehestan in Shiraz city. 2. THEORETICAL FRAMEWORK Nowadays, tourism is considered as the most comprehensive service industry of the world that has acquired a special place in economic, cultural, social, and political realms. Worldwide changes in the aftermath of the Second World War regarding the prevalence of urbanization, large cities, urban environmental pollutions, and the increase of leisure time resulted in the expansion of rural tourism. In the following decades, tourism was considered as a tool for rural development. Scientists have tried, by means of different patterns, to promote the role of tourism in the rural development. Therefore, it is possible to organically combine the two streams of destination identity research in the examination of a rural destination's image structure. Moreover, to construct a destination identity that represents localized features and lifestyles and elicits a holistic image suitable for tourism promotion, it is necessary to understand the role of rurality in rural tourism. 3. METHODOLOGY In this research, a descriptive-correlation method was used and in terms of purpose, it is an applied research. Data were analyzed with Structural Equation Modeling (LISREL) and Partial Least Squares method (PLS). According to Morgan table and stratified random sampling method, 385 tourists were selected. To collect data, questionnaire was used and its validity and reliability were examined by Cronbach's alpha, composite reliability and construct validity (confirmatory factor analysis). The levels of sustainability in the villages were done by selection of a number of important elements. Economic sustainability were measured by 5 items of the questionnaire including employment, living condition, earning money, migration of economic actors and land prices in the area. In order to investigate the social sustainability, a total of 4 items were applied; cultural exchange between people and tourists, tendency to addiction, public security and social links. Environmental sustainability indicator includes 5 items, i.e., air pollution, noise pollution, natural areas, the construction in pristine areas, traditional texture village of Qalat. 4. DISCUSSION In this research, most important aspects of sustainability have considered. In these villages, there are a range of positive and negative impacts in terms of rural tourism development. Results show social sustainability has highest impact factor (0.33). After that economic sustainability (0.22) and environmental sustainability (0.15) have more impact factor in the way of rural tourism development in selected villages of Drake region. Economic and environmental sustainable levels are lower than mean and social level is higher than mean. Moreover, the destination image as a modifier variable has positive and significant effect on economic sustainability, but it has not effect on social sustainability in Derak Dehestan and there is not significant relation between them. The Destination image has adverse and significant relation on environmental sustainability. 5. CONCLUSION The image destination can have important role for rural destination. There is a dynamic tension between tourists' imagination and tourism destinations. The tourists' consumption of and interaction with rural are dependent on offering rural areas that match tourists' expectations. This research show that destination image can impacts rural sustainability. It can be said the more we have positive image towards rural destination, the more we have sustainability. Given the findings, some suggestions are also presented, i.e., consider the role of local authority in the development of tourism as an effective factor to participate locals and raise awareness of the benefits of rural tourism development. Like other studies, this study has limitations. Including limited access to some tourists and inappropriateness of fitness model. It is suggested for future studies to examine the personal and demographic factors on people's willingness to visit and consider its impact on tourism development.

Творческий уровень освоения мстёрской лаковой миниатюрной живописи в вузе: типичные трудности и методы их преодоления

Analytical review of the typical difficulties of students of secondary vocational education and higher education (bachelor course) in the study of Mstyora lacquer miniature painting at the creative level of development is presented. It is noted that the artistic activity of young professionals, expressing themselves in creative activity and affecting the current state of the art of Mstyora, is determined in general by iconographic direction. The research urgency is caused by necessity of revealing the ways of preservation and development of unique art of Mstyora lacquer miniature painting, which is an integral part of the national artistic culture, in the framework of the professional education in this field. It is noted that in secondary vocational education one cannot in full formulate those qualities which will enable the graduate to independently solve the task of creating a holistic artistic image. Therefore, the continuation of education at bachelor course is considered a good opportunity for creative development of the future specialist. However, the author shows that at this time there is a trend in downwarding students’ interest to achieve the highest point of creative development. The causes of the problem and ways of its overcoming are discussed: removal or leveling.

Developing an e-lifestyle instrument for online shoppers in India: a confirmatory factor analytic approach

The purpose of this paper is to develop, refine and validate an e-lifestyle instrument for Indian online shoppers. Notably, in the internet era that we live in, it is absolutely imperative to understand, innovate and research the electronic lifestyles of Indians. Presently, online shopping in India is showing rapid growth and marketers are still trying to unravel and understand the lifestyles of online shoppers for purpose of segmentation, targeting and promotions. Be that as it may, Indian research scenario lacks an appropriate scale for such requirements, consequently shaping the basis of this study. Beyond refining and validating an e-lifestyle instrument, this study could provide marketers with insights on how to integrate e-lifestyles of the online shopper into marketing strategies. Altogether, the study is a significant beginning towards constructing a well-defined and more holistic image of factors influencing the Indian online shopper lifestyles.

Robust Topological Navigation via Convolutional Neural Network Feature and Sharpness Measure

Visual navigation for mobile robots has emerged in recent years. Among the various methods, topological navigation using visual information provides a scalable map representation for large-scale mapping and navigation. A topological map is essentially a graph with keyframes as its nodes and adjacency relations as its edges. Previous topological mapping uses local feature descriptors, such as scale-invariant feature transform or Speeded-Up Robust Features, to select keyframes in mapping, localization, and estimate relative pose. In practice, local features are not robust for severe motion blur or large illumination change. In this paper, we improve topological mapping to make it more efficient and robust. First, we use a convolutional neural network (CNN) feature as the holistic image representation. The CNN feature can be used to effectively retrieve keyframes that have similar appearance from a topological map, and it is robust to motion blur and illumination change. Thus, it improves the performance for place recognition and robot relocalization. Second, we use sharpness measure to select high-quality keyframes and avoid selecting blurry ones. Third, an efficient and robust non-rigid matching method, vector field consensus, is used for efficient geometric verification and to retrieve the most similar keyframe. The qualitative and quantitative experimental results demonstrate that our method is satisfactory.

More than Meets the Eye – Infrared Cameras in Open-Ended University Thermodynamics Labs

Educational research has found that students have challenges understanding thermal science. Undergraduate physics students have difficulties differentiating basic thermal concepts, such as heat, temperature, and internal energy. Engineering students have been found to have difficulties grasping surface emissivity as a thermal material property. One potential source of students’ challenges with thermal science is the lack of opportunity to visualize energy transfer in intuitive ways with traditional measurement equipment. Thermodynamics laboratories have typically depended on point measures of temperature by use of thermometers (detecting heat conduction) or pyrometers (detecting heat radiation). In contrast, thermal imaging by means of an infrared (IR) camera provides a real-time, holistic image. Here we provide some background on IR cameras and their uses in education, and summarize five qualitative investigations that we have used in our courses.

Approaches to the construction of cognitive linguistic–image models of knowledge representation for medical intelligent systems

Traditional linguistic–logical models in intelligent medical systems do not provide an exact match between the cognitive representation of an expert and the linguistic representation in a knowledge base, with regard to holistic visual images of diseases that meet certain definitions. The appearance of a patient is often important in medical diagnostics, in particular in hereditary diseases. However, we should note that there are no elaborated methods and tools to support special models that make it possible to use knowledge presented in verbal and figurative forms within the same formalism. Current national and foreign research and development in this field are mostly aimed at solving specific problems focused on a particular side of the problem. Clinical genetics is an area where the creation of systems based on a combination of verbalized and figurative knowledge can provide a qualitatively new level of diagnostics. Awareness of these factors results in the fact that the developed countries have become highly interested in medical-image analysis in recent years. However, these developments are not focused on the use of expert knowledge. One possible solution could be to construct a hybrid linguistic–image framework or ontological models that integrate qualitative and visual–image indicators for the formal description of diagnostically important clinical manifestations of diseases.

Linking the dots among destination images, place attachment, and revisit intentions: A study among British and Russian tourists

Limited evidence suggests that the incorporation of both image components (cognitive, affective, and conative) and holistic image is meaningful for predicting tourists' revisit intentions. Extending this line of research, the present study aims to unravel the relative influence that each component of image has directly and indirectly, via holistic image, on revisit intentions. In doing so, we incorporate two national samples (British and Russians) of diverse tourist profile and significantly different levels of visitation frequency to investigate place attachment as a moderator. Evidence from 1362 British and 1164 Russian tourists indicated that all image components have a positive indirect effect on revisit intention via holistic image, while conative has also a direct one. As expected, the image components rank differently for British and Russian tourists. The indirect effects of destination images on revisit intention, except conative, are conditional and, interestingly, most of these are stronger for tourists with low PA.

Learning Cascaded Deep Auto-Encoder Networks for Face Alignment

In this paper, we propose a new cascaded deep auto-encoder networks (CDAN) approach for face alignment. Our framework consists of a global exemplar-based deep auto-encoder network (GEDAN) and a series of localized deep auto-encoder networks (LDAN) in a cascaded fashion. The global network takes a low-resolution holistic facial image as input and generates a preliminary facial landmark configuration. The following localized networks sample pose-indexed local features around current landmark positions, and refine the landmark positions with increasingly higher image resolutions. Our network architectures are designed to achieve greater robustness against pose variations as well as higher landmark estimation accuracy. Experimental results on three datasets show that the proposed approach achieves superior alignment accuracy with real-time speed.

A holistic view of the use of corporate culture conveyed by internal marketing for enhancing stability, sustainability and consistency in service quality

While businesses worldwide are aiming increasingly on the sustainability in various business areas, customer service is by nature not consistent and stable, because it is delivered by human beings and, therefore, subject to their imperfections and influences on them. This can result in unstable, unsustainable and unpredictable service delivery. This article describes the corporate culture/service quality conceptualization as a basis for overcoming this by embedding and implementing the stability and sustainability of corporate culture to enhance the stability and sustainability of quality of service. This conceptual study demonstrates that a well-planned and maintained corporate culture, based on quality service delivery goals, is able to do exactly that under the initiative of the leadership. Although there are many articles referring to service quality, very few of them succeed in bringing sufficient aspects into account to be able to form a holistic image of enhancing stability, sustainability and consistency in service quality. Existing models and approaches were combined in a holistic conceptual approach. Keywords: service quality, corporate culture, stability, sustainability, customer perception, perceived quality, expectations, ACSI, internal marketing, relationship marketing, CSP, profit service chain. JEL Classification: L8, M14, M31, M30