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Relevant bibliographies by topics / Pose variations

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Journal articles

Academic literature on the topic 'Pose variations'

Author: Grafiati

Published: 4 May 2024

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Journal articles on the topic "Pose variations"

1

Du, Shan, and Rabab Ward. "Face recognition under pose variations." Journal of the Franklin Institute 343, no. 6 (2006): 596–613. http://dx.doi.org/10.1016/j.jfranklin.2006.08.006.

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2

Benjamin Dias, M., and Bernard F. Buxton. "Separating shape and pose variations." Image and Vision Computing 22, no. 10 (2004): 851–61. http://dx.doi.org/10.1016/j.imavis.2004.02.002.

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3

Palese, Marcella. "Variations by generalized symmetries of local Noether strong currents equivalent to global canonical Noether currents." Communications in Mathematics 24, no. 2 (2016): 125–35. http://dx.doi.org/10.1515/cm-2016-0009.

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Abstract We will pose the inverse problem question within the Krupka variational sequence framework. In particular, the interplay of inverse problems with symmetry and invariance properties will be exploited considering that the cohomology class of the variational Lie derivative of an equivalence class of forms, closed in the variational sequence, is trivial. We will focalize on the case of symmetries of globally defined field equations which are only locally variational and prove that variations of local Noether strong currents are variationally equivalent to global canonical Noether currents

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4

CHEN, SHAOKANG, BRIAN C. LOVELL, and TING SHAN. "ROBUST ADAPTED PRINCIPAL COMPONENT ANALYSIS FOR FACE RECOGNITION." International Journal of Pattern Recognition and Artificial Intelligence 23, no. 03 (2009): 491–520. http://dx.doi.org/10.1142/s0218001409007284.

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Recognizing faces with uncontrolled pose, illumination, and expression is a challenging task due to the fact that features insensitive to one variation may be highly sensitive to the other variations. Existing techniques dealing with just one of these variations are very often unable to cope with the other variations. The problem is even more difficult in applications where only one gallery image per person is available. In this paper, we describe a recognition method, Adapted Principal Component Analysis (APCA), that can simultaneously deal with large variations in both illumination and facia

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5

Osuna, Isaac Aaron Rodriguez, Pablo Cobelli, and Nahuel Olaiz. "Bubble Formation in Pulsed Electric Field Technology May Pose Limitations." Micromachines 13, no. 8 (2022): 1234. http://dx.doi.org/10.3390/mi13081234.

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Currently, increasing amounts of pulsed electric fields (PEF) are employed to improve a person’s life quality. This technology is based on the application of the shortest high voltage electrical pulse, which generates an increment over the cell membrane permeability. When applying these pulses, an unwanted effect is electrolysis, which could alter the treatment. This work focused on the study of the local variations of the electric field and current density around the bubbles formed by the electrolysis of water by PEF technology and how these variations alter the electroporation protocol. The

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6

Shanmuganathan, M., and T. Nalini. "Face Recognition using Nearest Neighbour and Nearest Mean Classification Framework : Empirical Analysis, Conclusions and Future Directions." Journal of Physics: Conference Series 2251, no. 1 (2022): 012010. http://dx.doi.org/10.1088/1742-6596/2251/1/012010.

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Abstract Human Face recognition algorithms have made huge progress in the last decade. In this manuscript, we have presented an approach for the implementation of a face recognition system in a successful manner by varying pose, scale, lighting, and age variation. The different empirical analysis was performed with various datasets for face detection and face identification. Face identification system detects efficiently segments and recognizes face in a cluttered sequence under varying pose, lighting and age variations. From this experimental analysis morphological model outperformed k-NNC, N

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7

Et. al., K. Suma,. "Dense Feature Based Face Recognition from Surveillance Video using Convolutional Neural Network." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (2021): 1436–49. http://dx.doi.org/10.17762/turcomat.v12i5.2040.

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Face Recognition is a field of identifying the person from the facial features and has wide application range in security, human computer interactions, finance etc. In recent years, many researchers have developed different algorithms to identify the Faces from various illumination variations and Pose variation, but these two problems remain unsolved in Face Recognition (FR) field. The Local Binary Pattern (LBP) has already proved its robustness in illumination variation. This paper proposes a four-patch Local Binary Pattern based FR utilizing Convolutional Neural Network (CNN) for ident

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8

HU, Yuan, Jingqi YAN, Wei LI, and Pengfei SHI. "3D Face Landmarking Method under Pose and Expression Variations." IEICE Transactions on Information and Systems E94-D, no. 3 (2011): 729–33. http://dx.doi.org/10.1587/transinf.e94.d.729.

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9

Drira, Hassen, Boulbaba Ben Amor, A. Srivastava, M. Daoudi, and R. Slama. "3D Face Recognition under Expressions, Occlusions, and Pose Variations." IEEE Transactions on Pattern Analysis and Machine Intelligence 35, no. 9 (2013): 2270–83. http://dx.doi.org/10.1109/tpami.2013.48.

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10

Zhou, Shaohua Kevin, and Rama Chellappa. "Image-based face recognition under illumination and pose variations." Journal of the Optical Society of America A 22, no. 2 (2005): 217. http://dx.doi.org/10.1364/josaa.22.000217.

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