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Relevant bibliographies by topics / Face and Object Recognition

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Dissertations / Theses

Academic literature on the topic 'Face and Object Recognition'

Author: Grafiati

Published: 6 September 2023

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Dissertations / Theses on the topic "Face and Object Recognition"

1

Gathers, Ann D. "DEVELOPMENTAL FMRI STUDY: FACE AND OBJECT RECOGNITION." Lexington, Ky. : [University of Kentucky Libraries], 2005. http://lib.uky.edu/ETD/ukyanne2005d00276/etd.pdf.

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Thesis (Ph. D.)--University of Kentucky, 2005.<br>Title from document title page (viewed on November 4, 2005). Document formatted into pages; contains xi, 152 p. : ill. Includes abstract and vita. Includes bibliographical references (p. 134-148).

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2

Nilsson, Linus. "Object Tracking and Face Recognition in Video Streams." Thesis, Umeå universitet, Institutionen för datavetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-58076.

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The goal with this project was to improve an existing face recognition system for video streams by using adaptive object tracking to track faces between frames. The knowledge of what faces occur and do not occur in subsequent frames was used to filter false faces and to better identify real ones. The recognition ability was tested by measuring how many faces were found and how many of them were correctly identified in two short video files. The tests also looked at the number of false face detections. The results were compared to a reference implementation that did not use object tracking. Two

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3

Banarse, D. S. "A generic neural network architecture for deformation invariant object recognition." Thesis, Bangor University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362146.

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4

Collin, Charles Alain. "Effects of spatial frequency overlap on face and object recognition." Thesis, McGill University, 2000. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=36896.

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There has recently been much interest in how limitations in spatial frequency range affect face and object perception. This work has mainly focussed on determining which bands of frequencies are most useful for visual recognition. However, a fundamental question not yet addressed is how spatial frequency overlap (i.e., the range of spatial frequencies shared by two images) affects complex image recognition. Aside from the basic theoretical interest this question holds, it also bears on research about effects of display format (e.g., line-drawings, Mooney faces, etc.) and studies examining the

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5

Higgs, David Robert. "Parts-based object detection using multiple views /." Link to online version, 2005. https://ritdml.rit.edu/dspace/handle/1850/1000.

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6

Mian, Ajmal Saeed. "Representations and matching techniques for 3D free-form object and face recognition." University of Western Australia. School of Computer Science and Software Engineering, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0046.

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[Truncated abstract] The aim of visual recognition is to identify objects in a scene and estimate their pose. Object recognition from 2D images is sensitive to illumination, pose, clutter and occlusions. Object recognition from range data on the other hand does not suffer from these limitations. An important paradigm of recognition is model-based whereby 3D models of objects are constructed offline and saved in a database, using a suitable representation. During online recognition, a similar representation of a scene is matched with the database for recognizing objects present in the scene . .

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Mian, Ajmal Saeed. "Representations and matching techniques for 3D free-form object and face recognition /." Connect to this title, 2006. http://theses.library.uwa.edu.au/adt-WU2007.0046.

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8

Holub, Alex David Perona Pietro. "Discriminative vs. generative object recognition : objects, faces, and the web /." Diss., Pasadena, Calif. : California Institute of Technology, 2007. http://resolver.caltech.edu/CaltechETD:etd-05312007-204007.

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9

Vilaplana, Besler Verónica. "Region-based face detection, segmentation and tracking. framework definition and application to other objects." Doctoral thesis, Universitat Politècnica de Catalunya, 2010. http://hdl.handle.net/10803/33330.

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One of the central problems in computer vision is the automatic recognition of object classes. In particular, the detection of the class of human faces is a problem that generates special interest due to the large number of applications that require face detection as a first step. In this thesis we approach the problem of face detection as a joint detection and segmentation problem, in order to precisely localize faces with pixel accurate masks. Even though this is our primary goal, in finding a solution we have tried to create a general framework as independent as possible of the type of

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10

Gunn, Steve R. "Dual active contour models for image feature extraction." Thesis, University of Southampton, 1996. https://eprints.soton.ac.uk/250089/.

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Active contours are now a very popular technique for shape extraction, achieved by minimising a suitably formulated energy functional. Conventional active contour formulations suffer difficulty in appropriate choice of an initial contour and values of parameters. Recent approaches have aimed to resolve these problems, but can compromise other performance aspects. To relieve the problem in initialisation, an evolutionary dual active contour has been developed, which is combined with a local shape model to improve the parameterisation. One contour expands from inside the target feature, the othe

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