object representation
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Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 664
Author(s):  
Samira Afzal ◽  
Laisa C. C. De Biase ◽  
Geovane Fedrecheski ◽  
William T. Pereira ◽  
Marcelo K. Zuffo

The Internet of Things (IoT) leverages added valued services by the wide spread of connected smart devices. The Swarm Computing paradigm considers a single abstraction layer that connects all kinds of devices globally, from sensors to super computers. In this context, the Low-Power Wide-Area Network (LPWAN) emerges, spreading out connection to the IoT end devices. With the upsides of long-range, low power and low cost, LPWAN presents major limitations regarding data transmission capacity, throughput, supported packet length and quantity per day limitation. This situation makes LPWAN systems with limited interoperability integrate with systems based on REpresentational State Transfer (REST). This work investigates how to connect web-based IoT applications with LPWANs. The analysis was carried out studying the number of packets generated for a use case of REST-based IoT over LPWAN, specifically the Swarm OS over LoRaWAN. The work also presents an analysis of the impact of using promising schemes for lower communication load. We evaluated Constrained Application Protocol (CoAP), Static Context Header Compression (SCHC) and Concise Binary Object Representation (CBOR) to make transmission over the restricted links of LPWANs possible. The attained results show the reduction of 98.18% packet sizes while using SCHC and CBOR compared to HTTP and JSON by sending fewer packets with smaller sizes.


Author(s):  
Rui M. Lourenco ◽  
Luis M. N. Tavora ◽  
Pedro A. A. Assuncao ◽  
Lucas A. Thomaz ◽  
Rui Fonseca-Pinto ◽  
...  

AbstractDuring the last decade, there has been an increasing number of applications dealing with multidimensional visual information, either for 3D object representation or feature extraction purposes. In this context, recent advances in light field technology, have been driving research efforts in disparity estimation methods. Among the existing ones, those based on the structure tensor have emerged as very promising to estimate disparity maps from Epipolar Plane Images. However, this approach is known to have two intrinsic limitations: (i) silhouette enlargement and (ii) irregularity of surface normal maps as computed from the estimated disparity. To address these problems, this work proposes a new method for improving disparity maps obtained from the structure-tensor approach by enhancing the silhouette and reducing the noise of planar surfaces in light fields. An edge-based approach is initially used for silhouette improvement through refinement of the estimated disparity values around object edges. Then, a plane detection algorithm, based on a seed growth strategy, is used to estimate planar regions, which in turn are used to guide correction of erroneous disparity values detected in object boundaries. The proposed algorithm shows an average improvement of 98.3% in terms of median angle error for plane surfaces, when compared to regular structure-tensor-based methods, outperforming state-of-the-art methods. The proposed framework also presents very competitive results, in terms of mean square error between disparity maps and their ground truth, when compared with their counterparts.


2021 ◽  
Author(s):  

In Dutch East India, photographic documentation for antiquities was as up-to-date as in Europe that was developed in the last half of the 19th century. Photography became a tool for archaeological surveys which resulted in thousands of enormous resources. In this paper, the historical background regarding how these old photographs were collected and how the material circulated within archaeological activities will be elaborated. The timeline studied is limited to pre-independence Indonesia with the subject mostly focused on Hindu-Buddhist remains. The method used is literature review of both relevant new publications as well as significant old publications. Its turns out that photographic surveys of archaeology in Indonesia during the colonial period developed from early archaeological activities into systematic institutional programs. The qualities of photography were appreciated in miscellaneous application and offered substantial benefits. Photography became a documentation medium, publication complementary, archive, and object representation and substitution. This historical background of photography in the context of Indonesian archaeology marks the significant value of these photographs so that it can be the foundation of preservation for the future. Di Hindia Belanda, dokumentasi fotografis pada tinggalan purbakala sangat mutakhir sebagaimana di Eropa yang dikembangkan sejak paruh terakhir abad ke-19 M. Fotografi menjadi perangkat untuk survei arkeologi yang menghasilkan ribuan sumber daya. Dalam tulisan ini, latar belakang sejarah terkait pengumpulan foto lama tersebut serta penggunaannya dalam berbagai aktifitas arkeologi akan dijabarkan. Lini masa yang dikaji dibatasi pada Indonesia pra-kemerdekaan dengan subjek yang berfokus pada tinggalan Hindu-Buddhis. Metode yang digunakan adalah kajian pustaka, baik terbitan terbaru yang relevan maupun terbitan lama yang penting. Ternyata survei fotografi pada arkeologi Indonesia selama periode kolonial berkembang sejak aktifitas arkeologis yang masih dini hingga menjadi program institusi yang sistematis. Kualitas fotografi juga diapresiasi dalam beragam penerapan serta menawarkan manfaat yang substansial, Fotografi menjadi media dokumentasi, pelengkap publikasi, arsip, serta representasi dan substitusi objek. Latar belakang sejarah fotografi dalam konteks arkeologi Indonesia semacam ini menjadikan nilai penting dari foto-foto tersebut sehingga dapat dijadikan fondasi dalam pelestarian untuk masa depan.


Author(s):  
Xiangjun Shen ◽  
Jinghui Zhou ◽  
Zhongchen Ma ◽  
Bingkun Bao ◽  
Zhengjun Zha

Cross-domain data has become very popular recently since various viewpoints and different sensors tend to facilitate better data representation. In this article, we propose a novel cross-domain object representation algorithm (RLRCA) which not only explores the complexity of multiple relationships of variables by canonical correlation analysis (CCA) but also uses a low rank model to decrease the effect of noisy data. To the best of our knowledge, this is the first try to smoothly integrate CCA and a low-rank model to uncover correlated components across different domains and to suppress the effect of noisy or corrupted data. In order to improve the flexibility of the algorithm to address various cross-domain object representation problems, two instantiation methods of RLRCA are proposed from feature and sample space, respectively. In this way, a better cross-domain object representation can be achieved through effectively learning the intrinsic CCA features and taking full advantage of cross-domain object alignment information while pursuing low rank representations. Extensive experimental results on CMU PIE, Office-Caltech, Pascal VOC 2007, and NUS-WIDE-Object datasets, demonstrate that our designed models have superior performance over several state-of-the-art cross-domain low rank methods in image clustering and classification tasks with various corruption levels.


Author(s):  
Amparo Bernal ◽  
Carlos Muñoz ◽  
Ana Sáez ◽  
Roberto Serrano-López

AbstractThe possibility of accessing free cartographic resources on the internet instead of creating their own digital object representation is a big advantage for architecture and engineering professionals in the surveying process of a construction or restoration project. The use of these products must be carried out with the guarantee that the precision of the site representation made from them is adapted to the level of detail required by each phase of the project. This paper compares graphically and statistically the accuracy of the topographic surfaces we can get from the LIDAR point clouds and the Digital Terrain Models (DTMs) of the National Centre for Geographic Information (CNIG by its Spanish acronym) that in Spain are available on the internet free of charge. We will use as a reference surface for comparison, the topographic map of the Digital Model Elevation (DEM) from the images captured by an unmanned aerial vehicle (UAV) processed with software based on algorithms of Structure from Motion (SfM). The study case for this comparative research will be the graphical survey of an archaeological site of funerary architecture made in 1939 during the Spanish Civil War. The monument is located near the city of Burgos (Spain) in an area with difficult access and restricted airspace, which makes difficult the fieldwork. The modeling of the surface has great importance for the graphic survey of the site, because its architectural configuration is adapted to the steep slope of the hillside. The purpose of this research is to check, if the surfaces provided through the Spanish open public cartographic resources are accurate enough to replace the mapping from UAV photogrammetry. Finally, if the outcomes can be extrapolated for widespread use of these resources for the site modeling of a project, according to the requirements of the different levels of development defined in the Building Information Modeling (BIM) methodology.


Author(s):  
Xavier E. Job ◽  
Louise P. Kirsch ◽  
Malika Auvray

AbstractInformation can be perceived from a multiplicity of spatial perspectives, which is central to effectively understanding and interacting with our environment and other people. Sensory impairments such as blindness are known to impact spatial representations and perspective-taking is often thought of as a visual process. However, disturbed functioning of other sensory systems (e.g., vestibular, proprioceptive and auditory) can also influence spatial perspective-taking. These lines of research remain largely separate, yet together they may shed new light on the role that each sensory modality plays in this core cognitive ability. The findings to date reveal that spatial cognitive processes may be differently affected by various types of sensory loss. The visual system may be crucial for the development of efficient allocentric (object-to-object) representation; however, the role of vision in adopting another’s spatial perspective remains unclear. On the other hand, the vestibular and the proprioceptive systems likely play an important role in anchoring the perceived self to the physical body, thus facilitating imagined self-rotations required to adopt another’s spatial perspective. Findings regarding the influence of disturbed auditory functioning on perspective-taking are so far inconclusive and thus await further data. This review highlights that spatial perspective-taking is a highly plastic cognitive ability, as the brain is often able to compensate in the face of different sensory loss.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
J. Verbe ◽  
P. G. Lindberg ◽  
P. Gorwood ◽  
L. Dupin ◽  
P. Duriez

AbstractBody representation distortion (BRD) is a core criterion of Anorexia Nervosa (AN), and is usually assessed subjectively, focusing on body shape. We aimed to develop a new assessment to evaluate body representation independently from socially-mediated body image, on a body part with low emotional salience (hands). In a monocentric open label pilot study, we measured hand representations based on explicit (verbal) and implicit (tactile) instructions. Participants, with eyes closed, had to point targeted locations (knuckles and nails of each finger) based on verbal instructions and tactile stimulations to evaluate body representations respectively. Ratios between hand width and finger length were compared between AN (n = 31) and controls (n = 31) and correlated with current body mass index, AN subtype and disease duration. To control that hand distortion was specific to body representation, we also assessed object representation. Hand representation’s width/length ratio was significantly increased in patients with AN, whereas no difference was found in object representation. We found no correlation between hand wideness and clinical traits related to eating disorders. Our results propose that BRD is not limited to body parts with high emotional salience, strengthening the hypothesis that anorexia nervosa is associated with profound unspecific BRD.


2021 ◽  
Author(s):  
Nicholas Martin Rosseinsky

The basic relationship between consciously-experienced representations, and material objects they represent, is hotly debated in some circles. But is it practically important? To investigate this, I introduce new symbolic notation, capable of labelling object, brain-perception, and conscious representation. Simple physics-based reasoning argues against identity of object and representation (rejecting e.g., direct realism). Nevertheless, a pivotal concern of the direct-realism school remains: how do we have knowledge of the world, if it’s only experienced indirectly? I sketch an indirect-school response, and review recent theoretical results showing how it simply doesn’t work in the dynamically-conventional setting (which is the hallmark of modern mainstream science). After illustrating how dynamically-conventional dysfunctions affect the foundations of science itself, I point to an experimentally-based resolution of knowledge-problems (and of the direct/indirect debate itself). Because the foundational problems for science affect its standing in society (for example, in its conflict with postmodernist ‘post-Truth’), the object-representation debate does turn out to have a practical significance, far beyond its conventional, academic/abstract/technical, framing.


2021 ◽  
Author(s):  
Andrew Marantan ◽  
Irina Tolkova ◽  
L. Mahadevan

Although the higher order mechanisms behind object representation and classification in the visual system are still not well understood, there are hints that simple shape primitives such as “curviness” might activate neural activation and guide this process. Drawing on elementary invariance principles, we propose that a statistical geometric object, the probability distribution of the normalized contour curvatures (NCC) in the intensity field of a planar image, has the potential to represent and classify categories of objects. We show that NCC is sufficient for discriminating between cognitive categories such as animacy, size and type, and demonstrate the robustness of this metric to variation in illumination and viewpoint, consistent with neurobiological constraints and psychological experiments. A generative model for producing artificial images with the observed NCC distributions highlights the key features that our metric captures and just as importantly, those that it does not. More broadly, our study points to the need for statistical geometric approaches to cognition that build in both the statistics and the natural invariances of the sensory world.


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