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Journal articles on the topic 'Part of an object'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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1

Ju, Ginny, and Irving Biederman. "Tests of a Theory of Human Image Understanding: Part I the Perception of Colored and Partial Objects." Proceedings of the Human Factors Society Annual Meeting 30, no. 3 (September 1986): 297–300. http://dx.doi.org/10.1177/154193128603000322.

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Object recognition can be conceptualized as a process in which the perceptual input is successfully matched with a stored representation of the object. A theory of pattern recognition, Recognition by Components(RBC) assumes that objects are represented as simple volumetric primatives (e.g., bricks, cylinders, etc.) in specifed relations to each other. According to RBC, speeded recognition should be possible from only a few components, as long as those components uniquely identify an object. Neither the full complement of an object's components, nor the object's surface characteristics (e.g., color and texture) need be present for rapid identification. The results from two experiments on the perception of briefly presented objects are offered for supporting the sufficiency of the theory. Line drawings are identified about as rapidly and as accurately as full color slides. Partial objects could be rapidly (though not optimally) identified. Complex objects are more readily identified than simple objects.

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Blickle, Thomas W., and Irving Biederman. "Tests of a Theory of Human Image Understanding: Part II. The Perception of Degraded Objects." Proceedings of the Human Factors Society Annual Meeting 30, no. 3 (September 1986): 301–5. http://dx.doi.org/10.1177/154193128603000323.

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Two experiments tested the predictions of a recent theory of object recognition (Recognition-By-Components or RBC). The first experiment supports RBC's predictions that recognition is accomplished by ascertaining the object's 3D components in their specified relations by utilizing certain nonaccidental 2D image properties. When object components were rendered nonrecoverable by deleting their nonaccidental properties recognition in an object naming task was interfered with more than when an equal amount of contour was deleted without erasing such properties. The second experiment supported RBC's assumption that vertices constitute one of these important nonaccidental properties. In a naming task objects were recognized more accurately when contour was deleted from midsegment than when an equal amount was deleted from the objects vertices.

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Pentland, Alex. "Part Segmentation for Object Recognition." Neural Computation 1, no. 1 (March 1989): 82–91. http://dx.doi.org/10.1162/neco.1989.1.1.82.

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Visual object recognition is a difficult problem that has been solved by biological visual systems. An approach to object recognition is described in which the image is segmented into parts using two simple, biologically-plausible mechanisms: a filtering operation to produce a large set of potential object “parts,” followed by a new type of network that searches among these part hypotheses to produce the simplest, most likely description of the image's part structure.

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4

Li, Yang, Jia Bao Wang, Jian Jiang Lu, Zhuang Miao, and Peng Fei Fang. "Object Tracking with Gradient Part-Based Models." Advanced Materials Research 490-495 (March 2012): 905–9. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.905.

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Partial occlusion and non-rigid variation are challenging problems in object tracking. To address this problem, robust gradient part-based models are proposed for object tracking in this paper. Our models constructed multiple well-chosen parts based on the gradient energy map of the object. And the local optimization algorithm, mean shift, is used to search the best locations of the multiple parts, which can be used to rectify the location of the tracked object by weighted feedback. Meanwhile, the models of the root and parts are updated online, which can improve tracking accuracy and robustness. Further, our models are easy to be embedded into different tracking algorithms and we implement the mean shift based on gradient part-based models. Experiments results show that our gradient part-based models are robust enough for object tracking, even though the objects are non-rigid or occluded.

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5

Leek, E. Charles, Irene Reppa, Elly Rodriguez, and Martin Arguin. "Surface but not volumetric part structure mediates three-dimensional shape representation: Evidence from part–whole priming." Quarterly Journal of Experimental Psychology 62, no. 4 (April 2009): 814–30. http://dx.doi.org/10.1080/17470210802303826.

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The decomposition of three-dimensional (3-D) objects into shape primitives consisting of geometric volumes is a key proposal of some theories of object recognition. It implicitly assumes that recognition involves volumetric completion—the derivation of a three-dimensional structure that comprises inferred shape properties, such as surfaces, that are not directly visible due to self-occlusion. The goal of this study was to test this claim. In Experiment 1 participants memorized novel objects and then discriminated these from previously unseen objects. Targets were preceded by primes containing a subset of object surfaces that either matched those visible in the whole objects or that could only be inferred through volumetric completion. The results showed performance benefits through priming from visible surfaces but not from inferred surfaces. In Experiment 2, we found equivalent priming for part-primes containing two visible surfaces from the same volumetric part and for primes containing one surface from each of two volumes. These results challenge the view that 3-D object recognition is mediated by shape primitives comprising geometric volumes. Instead, the results support an alternative model that proposes that 3-D shapes are represented as a non-volumetric surface-based structural description.

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6

Erdogan, Goker, Quanjing Chen, Frank E. Garcea, Bradford Z. Mahon, and Robert A. Jacobs. "Multisensory Part-based Representations of Objects in Human Lateral Occipital Cortex." Journal of Cognitive Neuroscience 28, no. 6 (June 2016): 869–81. http://dx.doi.org/10.1162/jocn_a_00937.

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The format of high-level object representations in temporal-occipital cortex is a fundamental and as yet unresolved issue. Here we use fMRI to show that human lateral occipital cortex (LOC) encodes novel 3-D objects in a multisensory and part-based format. We show that visual and haptic exploration of objects leads to similar patterns of neural activity in human LOC and that the shared variance between visually and haptically induced patterns of BOLD contrast in LOC reflects the part structure of the objects. We also show that linear classifiers trained on neural data from LOC on a subset of the objects successfully predict a novel object based on its component part structure. These data demonstrate a multisensory code for object representations in LOC that specifies the part structure of objects.

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7

Riabchenko, Ekaterina, and Joni-Kristian Kämäräinen. "Generative part-based Gabor object detector." Pattern Recognition Letters 68 (December 2015): 1–8. http://dx.doi.org/10.1016/j.patrec.2015.08.004.

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8

Václav, Štefan, Jozef Jurko, and Šimon Lecký. "Part as an Object of Assembly." Research Papers Faculty of Materials Science and Technology Slovak University of Technology 24, no. 38 (September 1, 2016): 57–65. http://dx.doi.org/10.1515/rput-2016-0039.

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Abstract We deal with static prearranged couples in practice quite often. Constructers are using them a lot to improve rigidity of product. Some examples are mentioned in this article. The paper also discusses the models of kinematic couples in plane and models of kinematic couples in space. Spatial movable and non-movable couples are commented on as well. The article particularly focuses on application of statics in the assembly in spatial couples (movable, non-movable) for intentional allowance fix which leads to a non-problem assembly. With fix like this, it is possible to manufacture selected parts in series while assuring non-problem assembly.

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9

Krivic, Jaka, and Franc Solina. "Part-level object recognition using superquadrics." Computer Vision and Image Understanding 95, no. 1 (July 2004): 105–26. http://dx.doi.org/10.1016/j.cviu.2003.11.002.

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10

Lazarev, Vladimir. "Bibliometrics, Scientometrics and Informetrics. Part 3. Object (Ending)." Science Management: Theory and Practice 3, no. 2 (June 30, 2021): 99–136. http://dx.doi.org/10.19181/smtp.2021.3.2.5.

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A simplified and sometimes vulgar understanding of the role of scientometrics in science management makes it necessary to better understand its essential characteristics. In this paper, scientometrics is considered in interrelations with bibliometrics and informetrics that are the fields of knowledge closest to it.In relation to bibliometrics, scientometrics and informetrics, this part discusses the representationof their object. Its reinterpretation using the modern broad meaning of the term “document” made us possible to come to the conclusion about (at least) the maximum convergence of interpretations of objects of bibliometrics, scientometrics and informetrics. In any case, such a comparative analysis of objects helps to identify both similarities and differences between these fields of knowledge, which is important, since their awareness is a very obvious initial condition for mutual conceptual enrichment (artificially diverged?) bibliometrics, scientometrics and informetrics with knowledge and concepts.The present, i. e. the third part of the paper provides examples of understanding the objects of bibliometrics, scientometrics, and informetrics using the modern, “broad” meaning of the concept of “document”. It is shown that with the use of this approach, the interpretations of the objects of bibliometrics, scientometrics and informetrics are even closer than with the use of the traditional one. Also, the cognitive capabilities of bibliometrics, scientometrics and informetrics are potentially expanded in this case. The ways of possible further research in this direction are outlined, taking into account the V. S. Stepin’s viewpoints on the subject of research as a concept dependent on the applied methods, and on the empirical object asthe essence allocated in connection with the tasks of cognition.

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Maltchenko, S. Z. "The bio-objects project. Part I: the object data model core elements." Bioinformatics 14, no. 6 (July 1, 1998): 479–85. http://dx.doi.org/10.1093/bioinformatics/14.6.479.

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Lazarev, Vladimir. "Bibliometrics, scientometrics and informetrics. Part 2. Object." Science Management: Theory And Practice 3, no. 1 (March 25, 2021): 80–105. http://dx.doi.org/10.19181/smtp.2021.3.1.5.

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A simplified and sometimes vulgar understanding of the role of scientometrics in science management makes it necessary to better understand its essential characteristics. In this paper, scientometrics is considered in interrelations with bibliometrics and informetrics that are the fields of knowledge closest to it.In relation to bibliometrics, scientometrics and informetrics, this part discusses the representationof their object. Its reinterpretation using the modern broad meaning of the term “document” made us possible to come to the conclusion that there is (at least) the maximum convergence of interpretations of objects of bibliometrics, scientometrics and informetrics. In any case, such a comparative analysis of objects helps to identify both similarities and differences between these fields of knowledge, which is important, since their awareness is a very obvious initial condition for mutual conceptual enrichment (artificially diverged?) bibliometrics, scientometrics and informetrics with knowledge and concepts.Part 2 of the present paper provides examples of treating the objects of bibliometrics, scientometricsand informetrics using traditional interpretations of the concept of a “document”, followed by brief a review of the reinterpretation of this concept. However, consideration of the relationship of a “document” and “information” is much more detailed in the present work than it was performed in the author’s previous paper on this topic.

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13

Guelzim, Ibrahim, Amina Amkoui, and Hammadi Nait-Charif. "Part-Based Lumbar Vertebrae Tracking in Videofluoroscopy Using Particle Filter." International Journal of Computer Vision and Image Processing 10, no. 2 (April 2020): 29–44. http://dx.doi.org/10.4018/ijcvip.2020040103.

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Vertebrae tracking in videofluoroscopy is a challenging problem because of the low quality ‎of ‎image ‎sequences, like poor image contrast, ambiguous geometry details, and vertebrae rotation. The aim of this article is to tackle this problem by ‎proposing a ‎method for rigid object tracking based on the ‎fragmentation of the tracked object. The proposed method ‎is based on the particle filter using the calculation of the similarity between the ‎respective‏ ‏fragments of ‎objects instead of the whole objects. The similarity measures used are the Jaccard index, the ‎correlation ‎coefficient, and the Bhattacharyya coefficient. The tracking starts with a semi-automatic initialization. ‎The results show that the fragments-based object tracking method outperforms the classical ‎method ‎‎(without fragmentation) for each of the used similarity measures. The results show that the ‎tracking based on the Jaccard index is more stable and outperforms methods based on ‎other similarity ‎measures.‎

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14

West, Donna E. "The Primacy of Index in Naming Paradigms. Part I." Respectus Philologicus 27, no. 32 (April 25, 2015): 23–32. http://dx.doi.org/10.15388/respectus.2015.27.32.2.

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This analysis highlights semiotic naming differences between pronouns, nouns, and verbs. It capitalizes on the pivotal role of Peirce's Object in assigning names, and the special character of pronouns to hasten notice of Objects. It showcases Peirce's indexical sign as an individuating instrument, by arguing that nouns do not name the Object uniquely. The indexical sign alone forces attention on unique entities. Their capacity to invoke notice of shifting places via pronouns/verbs is paramount.The findings indicate a particular developmental course: a noticed “something,” classified object, individuated sequence of actions. The naming begins with the most pure Indexes (pronouns), then nouns (which draw upon similar features); afterwards, the verbs emerge to name dynamic event profiles. This illustrates the indispensability of index in the naming process. Advances in deictic individuation establish and reinforce joint attentional ventures: co-signers are compelled not merely to attend to the same Object, but to recognize distinctive participant roles in event structures.

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15

West, Donna E. "The Primacy of Index in Naming Paradigms. Part II." Respectus Philologicus 28, no. 33 (October 25, 2015): 11–21. http://dx.doi.org/10.15388/respectus.2015.28.33.1.

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This analysis highlights the semiotic naming differences between the pronouns, nouns, and verbs. It capitalizes on the role of Peirce’s Object in assigning names and the special character of pronouns and verbs to hasten notice of Objects. It showcases Peirce’s indexical sign as an individuating instrument, by arguing that nouns do not name the Object uniquely. The invoking notice of shifting places via pronouns/verbs is paramount. Naming begins with the most pure Indexes (pronouns), then nouns (which draw upon similar features); afterward, verbs emerge to name the dynamic event profile, illustrating the indispensability of the index. The advances in deictic individuation establish and reinforce the joint attentional ventures: co-signers are compelled not merely to attend to the same Object but to recognize distinctive participant roles in events as well.

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16

Ha, Ngo Duong, Ikuko Shimizu, and Pham The Bao. "Tracking Objects Based on Multiple Particle Filters for Multipart Combined Moving Directions Information." Computational Intelligence and Neuroscience 2020 (December 16, 2020): 1–13. http://dx.doi.org/10.1155/2020/8839725.

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Object tracking is an important procedure in the computer vision field as it estimates the position, size, and state of an object along the video’s timeline. Although many algorithms were proposed with high accuracy, object tracking in diverse contexts is still a challenging problem. The paper presents some methods to track the movement of two types of objects: arbitrary objects and humans. Both problems estimate the state density function of an object using particle filters. For the videos of a static or relatively static camera, we adjusted the state transition model by integrating the movement direction of the object. Also, we propose that partitioning the object needs tracking. To track the human, we partitioned the human into N parts and, then, tracked each part. During tracking, if a part deviated from the object, it was corrected by centering rotation, and the part was, then, combined with other parts.

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17

Chen, Yuh-Min, R. Allen Miller, and Dik Lun Lee. "Object-Oriented Part Model for Geometric Reasoning." Integrated Computer-Aided Engineering 1, no. 5 (June 1, 1994): 375–95. http://dx.doi.org/10.3233/ica-1994-1502.

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18

Kuang, Xiaoqin, Nong Sang, and Changxin Gao. "Object localization with mid-level part detectors." Neurocomputing 212 (November 2016): 58–64. http://dx.doi.org/10.1016/j.neucom.2016.02.080.

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19

Cohen, Malcolm. "Object orientation and Fortran 2002: part I." ACM SIGPLAN Fortran Forum 16, no. 3 (December 1997): 5–10. http://dx.doi.org/10.1145/274104.274107.

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20

Yanling Chi and M. K. H. Leung. "Part-Based Object Retrieval in Cluttered Environment." IEEE Transactions on Pattern Analysis and Machine Intelligence 29, no. 5 (May 2007): 890–95. http://dx.doi.org/10.1109/tpami.2007.1076.

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21

Felzenszwalb, Pedro, Ross Girshick, David McAllester, and Deva Ramanan. "Visual object detection with deformable part models." Communications of the ACM 56, no. 9 (September 2013): 97–105. http://dx.doi.org/10.1145/2494532.

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Felzenszwalb, Pedro, Ross Girshick, David McAllester, and Deva Ramanan. "Visual object detection with deformable part models." Communications of the ACM 56, no. 9 (September 1, 2013): 97. http://dx.doi.org/10.1145/2500468.2494532.

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23

Yi, Li, Haibin Huang, Difan Liu, Evangelos Kalogerakis, Hao Su, and Leonidas Guibas. "Deep part induction from articulated object pairs." ACM Transactions on Graphics 37, no. 6 (January 10, 2019): 1–15. http://dx.doi.org/10.1145/3272127.3275027.

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24

Gadeski, Etienne, Hamidreza Odabai Fard, and Hervé Le Borgne. "GPU deformable part model for object recognition." Journal of Real-Time Image Processing 14, no. 2 (September 4, 2014): 279–91. http://dx.doi.org/10.1007/s11554-014-0447-5.

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25

Lu, ChengEn, Nagesh Adluru, Haibin Ling, Guangxi Zhu, and Longin Jan Latecki. "Contour based object detection using part bundles." Computer Vision and Image Understanding 114, no. 7 (July 2010): 827–34. http://dx.doi.org/10.1016/j.cviu.2010.03.009.

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26

Zhao, Chaoyang, Jinqiao Wang, Guibo Zhu, Yi Wu, and Hanqing Lu. "Learning weighted part models for object tracking." Computer Vision and Image Understanding 143 (February 2016): 173–82. http://dx.doi.org/10.1016/j.cviu.2015.10.004.

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27

Stout, Brian, Michel Nevière, and Evgeny Popov. "Mie scattering by an anisotropic object Part II Arbitrary-shaped object: differential theory." Journal of the Optical Society of America A 23, no. 5 (May 1, 2006): 1124. http://dx.doi.org/10.1364/josaa.23.001124.

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28

Bartczak-Meszyńska, Aleksandra. "What makes you move? A minimalist study of object displacement in English Double Object Construction." Linguistics Beyond and Within (LingBaW) 1 (December 30, 2015): 6–24. http://dx.doi.org/10.31743/lingbaw.5621.

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The aim of this paper is to analyse the displacement phenomena the direct and indirect objects in the English Double Object Construction (DOC) can undergo. The focus is on the movement out of the DOC to the sentence initial position. The analysis concerns not only globally acceptable Goal-Theme object sequence but also the Theme-Goal DOC, which grammaticality is restricted only to a few British English dialects. The processes affecting the objects in the Prepositional Construction are also mentioned. The initial part of the paper is devoted to the underlying syntactic representations of the DOC in English. Following, e.g. Citko (2011), Cuervo (2003), Pylkkännen (2002, 2008), a representation with the Low Applicative Phrase has been adopted. The exact case valuation mechanism for relevant objects (as proposed by Bondaruk and Bartczak-Meszyńska (2014)) has been established. The remaining part of this paper contains a detailed discussion of the derivation of particular object initial sentences with the DOC in the active and in the passive and the interplay between passivisation and topicalisation, as the triggers of the object fronting.

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Skytsiouk, Volodymyr, and Tatiana Klotchko. "PHANTOM MODEL OF DISTRIBUTION OF VIRAL OBJECTS IN A PANDEMIC. PART 3." Bulletin of Kyiv Polytechnic Institute. Series Instrument Making, no. 61(1) (June 30, 2021): 101–8. http://dx.doi.org/10.20535/1970.61(1).2021.237113.

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The article states that the nature of the virus's interaction with objects during its spread in any environment is a significant problem. Therefore, taking into account the peculiarities of such a complex fractional composition of flows can make it possible to determine the nature of the interaction of the object, in particular biological, with complex particles of viral flows when touching. The author's previous works consider the peculiarities of the spread of viruses in the surrounding space of the pandanus zone of the object under the condition of a single fraction of the particle, ie in the near-surface layer. Of course, to better understand the nature of the interaction of viral flows with objects of possible infection, it is necessary to analyze the processes of virion’s touching to the cell surface of a biological object. The studied regularities of the occurrence of motion forces in environment’s space made it possible to determine the geometric parameters of the spread of viral formations near the object’s surface. The main purpose of this study was to continue to create a model of interaction of complex flows with different fractions that are carriers of viruses as material particles in the environment, in terms of modeling the motion and touching the surface of the object at different types of touch depending on their interaction. The mechanical movement of the virus during contact, rather than stages, as in biological processes, is considered. The nature of the interaction of complex viruses’s streams with objects of biological origin is modeled. To study the peculiarities of the interaction of the virion with the cell surface of a biological object, it is necessary to consider the flow complex of particles of different fractions, i.e. microstructures of virions that accompany drip suspension flows of body fluids and foreign dust particles. Thus, we can distinguish the motion of a complex of particles that comes into contact with object’s surface, as well as the possibility of breaking out individual microparticles, virions, which can emerge from the complex flow and propagate separately from others. At the same time, the dependences of the energy complex, which forms the flow of complex elements-particles of different fractions, which can take into account the range of flow propagation and features of motion kinematics, are determined. In further research, the phantom model of the propagation of fluxes of viral objects in space requires modeling the temporal parameters of the motion of fluxes of complex particles during the propagation to the object’s surface of various origins, including biological object.

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Zhang, Yabin, Kui Jia, and Zhixin Wang. "Part-Aware Fine-Grained Object Categorization Using Weakly Supervised Part Detection Network." IEEE Transactions on Multimedia 22, no. 5 (May 2020): 1345–57. http://dx.doi.org/10.1109/tmm.2019.2939747.

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31

Liu, Xiaohu, Yichuang Luo, Keding Yan, Jianfei Chen, and Zhiyong Lei. "Part‐MOT: A multi‐object tracking method with instance part‐based embedding." IET Image Processing 15, no. 11 (May 7, 2021): 2521–31. http://dx.doi.org/10.1049/ipr2.12240.

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32

Wu, Xiaojun. "HETEROGENEOUS MATERIAL OBJECT MODELING FOR 3D CAD PART." Chinese Journal of Mechanical Engineering 40, no. 05 (2004): 111. http://dx.doi.org/10.3901/jme.2004.05.111.

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RUAN, Zhiwei, Guijin WANG, Xinggang LIN, Jing-Hao XUE, and Yong JIANG. "Deformable Part-Based Model Transfer for Object Detection." IEICE Transactions on Information and Systems E97.D, no. 5 (2014): 1394–97. http://dx.doi.org/10.1587/transinf.e97.d.1394.

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Wu, Jue, Wenchao Cai, and Albert C. S. Chung. "POSIT: Part-based object segmentation without intensive training." Pattern Recognition 43, no. 3 (March 2010): 676–84. http://dx.doi.org/10.1016/j.patcog.2009.07.013.

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Bai, Xiao, Peng Ren, Huigang Zhang, and Jun Zhou. "An incremental structured part model for object recognition." Neurocomputing 154 (April 2015): 189–99. http://dx.doi.org/10.1016/j.neucom.2014.12.004.

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36

Mitrani, Judith L. "On Adhesive Pseudo-Object Relations Part II: Illustration." Contemporary Psychoanalysis 31, no. 1 (January 1995): 140–65. http://dx.doi.org/10.1080/00107530.1995.10746902.

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Felzenszwalb, P. F., R. B. Girshick, D. McAllester, and D. Ramanan. "Object Detection with Discriminatively Trained Part-Based Models." IEEE Transactions on Pattern Analysis and Machine Intelligence 32, no. 9 (September 2010): 1627–45. http://dx.doi.org/10.1109/tpami.2009.167.

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38

Forsyth, David. "Object Detection with Discriminatively Trained Part-Based Models." Computer 47, no. 2 (February 2014): 6–7. http://dx.doi.org/10.1109/mc.2014.42.

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39

Krikorian, H. F. "Introduction to object-oriented systems engineering, part 2." IT Professional 5, no. 3 (May 2003): 49–55. http://dx.doi.org/10.1109/mitp.2003.1202235.

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40

Moore, Cathleen M., Steven Yantis, and Barry Vaughan. "Object-Based Visual Selection: Evidence From Perceptual Completion." Psychological Science 9, no. 2 (March 1998): 104–10. http://dx.doi.org/10.1111/1467-9280.00019.

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A large body of evidence suggests that visual attention selects objects as well as spatial locations. If attention is to be regarded as truly object based, then it should operate not only on object representations that are explicit in the image, but also on representations that are the result of earlier perceptual completion processes. Reporting the results of two experiments, we show that when attention is directed to part of a perceptual object, other parts of that object enjoy an attentional advantage as well. In particular, we show that this object-specific attentional advantage accrues to partly occluded objects and to objects defined by subjective contours. The results corroborate the claim that perceptual completion precedes object-based attentional selection.

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41

Shevchenko, Eleonora A., and Andrej A. Lukashev. "On the Actual Basis for Establishing the Boundaries of Cultural Heritage in the form of Places of Interest. Part 1." Scientific journal “ACADEMIA. ARCHITECTURE AND CONSTRUCTION”, no. 1 (March 18, 2019): 62–69. http://dx.doi.org/10.22337/2077-9038-2019-1-62-69.

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Disputes around such a type of cultural heritage object as "Places of Interest" have not ceased since the adoption, in 2002, of Federal Law No. 73-FZ "On objects of cultural heritage (historical and cultural monuments) of the peoples of the Russian Federation", which introduced it this new kind of cultural heritage object. The main problem lies in a deep misunderstanding of the meaning, the essence, the importance for the preservation of the historical environment of the populated areas, as the actual genome of the city of this unique Object of cultural heritage. The purpose of this article is to reveal the deep essence of one of the types of cultural heritage object, often identified with such a category of "Objects" heritage as a historical settlement and, often, equated with such kind of cultural heritage object as "Monument". The importance of defining it as an integral object of real estate with the most complex composition and structure is explained by the need to take urgent measures to preserve the authenticity and uniqueness of the populated areas and territories involved in the strategic development of Russia. The interdepartmental nature of Landmarks is proved, which determines its interdisciplinary peculiarities of determining the boundaries of a given object, which are at the same time the boundaries of its territory. Considered all listed in the law of varieties of Sightseeing Places.

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Park, Ji Hun, and Sung Hun Park. "Object Movement Computation from Two Images." Applied Mechanics and Materials 752-753 (April 2015): 1085–89. http://dx.doi.org/10.4028/www.scientific.net/amm.752-753.1085.

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This paper presents a new object movement computation method using ray vectors generated from two cameras. We compute camera's internal and external parameters of the input images using computed values from partially overlapping input image frames which has the same corresponding fixed feature points. This is achieved by computing fixed points in the environment, camera distortion values and internal and external parameters from stationary objects. Ray vectors cast from each camera to feature points keep camera external parameter values. Using computed camera external parameters, a tracked object's rigid object movement is estimated using maximum likelihood estimation by setting projected intersection points between ray vectors as a part of objective function. Our method is demonstrated and the results are compared to our another movement computation algorithm.

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Carota, Francesca, Rachel Moseley, and Friedemann Pulvermüller. "Body-part-specific Representations of Semantic Noun Categories." Journal of Cognitive Neuroscience 24, no. 6 (June 2012): 1492–509. http://dx.doi.org/10.1162/jocn_a_00219.

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Word meaning processing in the brain involves ventrolateral temporal cortex, but a semantic contribution of the dorsal stream, especially frontocentral sensorimotor areas, has been controversial. We here examine brain activation during passive reading of object-related nouns from different semantic categories, notably animal, food, and tool words, matched for a range of psycholinguistic features. Results show ventral stream activation in temporal cortex along with category-specific activation patterns in both ventral and dorsal streams, including sensorimotor systems and adjacent pFC. Precentral activation reflected action-related semantic features of the word categories. Cortical regions implicated in mouth and face movements were sparked by food words, and hand area activation was seen for tool words, consistent with the actions implicated by the objects the words are used to speak about. Furthermore, tool words specifically activated the right cerebellum, and food words activated the left orbito-frontal and fusiform areas. We discuss our results in the context of category-specific semantic deficits in the processing of words and concepts, along with previous neuroimaging research, and conclude that specific dorsal and ventral areas in frontocentral and temporal cortex index visual and affective–emotional semantic attributes of object-related nouns and action-related affordances of their referent objects.

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Schendan, Haline E., and Marta Kutas. "Neurophysiological Evidence for the Time Course of Activation of Global Shape, Part, and Local Contour Representations during Visual Object Categorization and Memory." Journal of Cognitive Neuroscience 19, no. 5 (May 2007): 734–49. http://dx.doi.org/10.1162/jocn.2007.19.5.734.

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Categorization of visual objects entails matching a percept to long-term representations of structural knowledge. This object model selection is central to theories of human visual cognition, but the representational format(s) is largely unknown. To characterize these neural representations, event-related brain potentials (ERPs) to fragmented objects during an indirect memory test were compared when only local contour features, but not global shapes of the object and its parts, differed between encoding and retrieval experiences. The ERP effects revealed that the format of object representations varies across time according to the particular neural processing and memory system currently engaged. An occipito-temporal P2(00) showed implicit memory modulation to items that repeatedly engaged similar perceptual grouping processes but not items that merely reinstantiated visual features. After 500 msec, memory modulation of a late positive complex, indexing secondary categorization and/or explicit recollection processes, was sensitive to local contour changes. In between, a frontocentral N350, indexing the model selection and an implicit perceptual memory system, showed reactivation of object representations whenever the same global shapes were reactivated, despite local feature differences. These and prior N350 findings provide direct neurophysiological evidence that the neural representations supporting object categorization include knowledge beyond local contours and about higher-order perceptual structures, such as the global shapes of the object and its parts, that can differ between object views. The N350 is proposed to index a second state of interactive, recurrent, and feedback processing in occipital and ventral temporal neocortex supporting higher-order cognitive abilities and phenomenological awareness with objects.

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Rakhmatova, Alisa Mukhamatovna. "Lyrical object and other lyrical characters in J. Brodsky’s cycle “Part of Speech”." Филология: научные исследования, no. 4 (April 2021): 19–27. http://dx.doi.org/10.7256/2454-0749.2021.4.35303.

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The object of this research is the poetics of J. Brodsky's cycle “Part of Speech” as literary unity. The subject of this research is the subjective organization of poems included in the cycle “Part of Speech”. Special attention is given to the nature of value attitude of the lyrical object towards other characters depicted in poems of the cycle. Such attitude is viewed as an aspect of authorial artistic reflection and assessment of depicted reality. Following the footsteps of S. N. Broytman, the author interprets the lyrical object as a speech bearer, as well as the main (encompassing other) perspective on the world in the poem. The lyrical character is a supported character, being assessed by the lyrical object (lyrical characters include a “lyrical addressee” and “lyrical You”). The scientific novelty of this research consists in viewing the nature of value attitude of the lyrical objects towards other lyrical characters in the “Part of Speech” as an aspect of poetics of the cycle as literary unity (previous studies were dedicated only to separate poems of J. Brodsky’s cycle). The analysis of selected texts of the cycle indicates the specific nature of the relationship between lyrical object and other characters depicted in the poems: 1. the relationship of the lyrical object with other characters (the lyrical heroine, “You”, etc.) is built as an anti-dialogue, demonstrating total loneliness of the lyrical object; 2. The theme of loneliness in the cycle also intersects with the artistic images for yourself; 3. in the “Part of Speech”, the forms of indirect representation of the lyric object (when the lyrical subject refers to himself as another) also point at his self-centeredness, loneliness, and disruption of ties with others.

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Akbari Sekehravani, Ehsan, Eduard Babulak, and Mehdi Masoodi. "Flying object tracking and classification of military versus nonmilitary aircraft." Bulletin of Electrical Engineering and Informatics 9, no. 4 (August 1, 2020): 1394–403. http://dx.doi.org/10.11591/eei.v9i4.1843.

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Tracking of moving objects in a sequence of images is one of the important and functional branches of machine vision technology. Detection and tracking of a flying object with unknown features are important issues in detecting and tracking objects. This paper consists of two basic parts. The first part involves tracking multiple flying objects. At first, flying objects are detected and tracked, using the particle filter algorithm. The second part is to classify tracked objects (military or nonmilitary), based on four criteria; Size (center of mass) of objects, object speed vector, the direction of motion of objects, and thermal imagery identifies the type of tracked flying objects. To demonstrate the efficiency and the strength of the algorithm and the above system, several scenarios in different videos have been investigated that include challenges such as the number of objects (aircraft), different paths, the diverse directions of motion, different speeds and various objects. One of the most important challenges is the speed of processing and the angle of imaging.

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Ferro, Floriana. "Object-Oriented Ontology’s View of Relations: a Phenomenological Critique." Open Philosophy 2, no. 1 (November 1, 2019): 566–81. http://dx.doi.org/10.1515/opphil-2019-0040.

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AbstractThis paper is focused on the possibility of a dialogue between Object-Oriented Ontology (OOO) and phenomenology, a dialogue concerning the problem of objects and relations. In the first part, the author shows what is interesting in OOO from a phenomenological perspective and why it should be considered as a challenge for contemporary philosophy. The second part develops the phenomenological perspective of the author, a perspective based on Merleau-Ponty’s “carnal” phenomenology, as well as some suggestions coming from the Italian school of Gaetano Kanizsa. The third part is dedicated to the objections of the author to the OOO view regarding the separation between objects and relations: a separation which leads to Harman’s quadruple object. In the concluding portion, the author shows that, despite evident differences between phenomenological and OOO’s views of relations, OOO offers new starting points for phenomenological reflections, thanks to its specific focus on objects and its pluralistic view of reality.

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Zafar, Adeel, and Umar Khalid. "Detect-and-describe: Joint learning framework for detection and description of objects." MATEC Web of Conferences 277 (2019): 02028. http://dx.doi.org/10.1051/matecconf/201927702028.

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Traditional object detection answers two questions; “what” (what the object is?) and “where” (where the object is?). “what” part of the object detection can be fine grained further i-e. “what type”, “what shape” and “what material” etc. This results in shifting of object detection task to object description paradigm. Describing object provides additional detail that enables us to understand the characteristics and attributes of the object (“plastic boat” not just boat, “glass bottle” not just bottle). This additional information can implicitly be used to gain insight about unseen objects (e.g. unknown object is “metallic”, “has wheels”), which is not possible in traditional object detection. In this paper, we present a new approach to simultaneously detect objects and infer their attributes, we call it Detectand- Describe (DaD) framework. DaD is a deep learning-based approach that extends object detection to object attribute prediction as well. We train our model on aPascal train set and evaluate our approach on aPascal test set. We achieve 97.0% in Area Under the Receiver Operating Characteristic Curve (AUC) for object attributes prediction on aPascal test set. We also show qualitative results for object attribute prediction on unseen objects, which demonstrate the effectiveness of our approach for describing unknown objects.

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Mohamed, Emad. "Object and subject Heavy-NP shift in Arabic." Research in Corpus Linguistics 2 (2014): 23–33. http://dx.doi.org/10.32714/ricl.02.03.

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In order to examine whether Arabic has Heavy Noun Phrase Shifting (HNPS), I have extracted from the Prague Arabic Dependency Treebank a data set in which a verb governs either an object NP and an Adjunct Phrase (PP or AdvP) or a subject NP and an Adjunct Phrase. I have used binary logistic regression where the criterion variable is whether the subject/object NP shifts, and used as predictor variables heaviness (the number of tokens per NP, adjunct), part of speech tag, verb disposition (ie. whether the verb has a history of taking double objects or sentential objects), NP number, NP definiteness, and the presence of referring pronouns in either the NP or the adjunct. The results show that only object heaviness and adjunct heaviness are useful predictors of object HNPS, while subject heaviness, adjunct heaviness, subject part of speech tag, definiteness, and adjunct head POS tags are active predictors of subject HNPS. I also show that HNPS can in principle be predicted from sentence structure.

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Ozolinya, L. V. "Indirect object in Manchu-Tungus languages: structural and semantic aspect (in the Orok language)." Sibirskiy filologicheskiy zhurnal, no. 3 (2020): 243–60. http://dx.doi.org/10.17223/18137083/72/19.

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For the first time, the paper provides the analysis of the Oroc language object as a syntactic unit combining the semantic and functional aspects of transitive or non-transitive verbs. In the Manchu-Tungus languages, the object is found to be expressed in the morphological forms of the case: direct – in the accusative case and the possessive forms of the designative case, indirect – in the forms of oblique cases. Constructions with indirect objects, the positions of which are filled with case forms of nouns, designate the objects on which the action is aimed, objects from which the action is sent or evaded, objects-addresses, objectsinstruments, etc. Both transitive or non-transitive verbs can take the position of the predicate. The necessary (direct object) and permissible (indirect object) composition of objects in the verb is determined by its valences: bivalent verbs open subjective (subject) and objective (direct object) valences; trivalent verbs reveal subjective, subjective-objective (part of the subject or indirect subject) and objective (indirect object) valences.

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