Relevant bibliographies by topics / 2D/3D object discovery

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  1. Dissertations / Theses

Academic literature on the topic '2D/3D object discovery'

Author: Grafiati
Published: 8 March 2025

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Dissertations / Theses on the topic "2D/3D object discovery"

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Kara, Sandra. "Unsupervised object discovery in images and video data." Electronic Thesis or Diss., université Paris-Saclay, 2025. http://www.theses.fr/2025UPASG019.

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Cette thèse explore les méthodes d'apprentissage auto-supervisé pour la localisation d'objets, communément appelées « Object Discovery ». La localisation d'objets dans les images et les vidéos est un élément essentiel des tâches de vision par ordinateur telles que la détection, la ré-identification, le suivi, etc. Les algorithmes supervisés actuels peuvent localiser (et classifier) les objets avec précision, mais ils sont coûteux en raison de la nécessité de données annotées. Le processus d'étiquetage est généralement répété pour chaque nouvelle donnée ou catégorie d'intérêt, limitant ainsi le
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Shao, Zhimin. "3D/2D object recognition from surface patterns." Thesis, University of Surrey, 1997. http://epubs.surrey.ac.uk/844055/.

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Attributed Relational Graph (ARG) is a powerful representation for model based object recognition due to its inherent robustness in handling noisy and incomplete data. In the past few years, the availability of efficient ARG matching algorithms and their theoretical underpinnings have greatly contributed to many successful applications of ARG representation in tackling high level vision problems. During my past three year investigation into object recognition using ARG representation, we have developed a number of novel theories and techniques in the subject area. Some are image processing tec
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Sirtkaya, Salim. "Moving Object Detction In 2d And 3d Scenes." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/2/12605310/index.pdf.

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This thesis describes the theoretical bases, development and testing of an integrated moving object detection framework in 2D and 3D scenes. The detection problem is analyzed in stationary and non-stationary camera sequences and different algorithms are developed for each case. Two methods are proposed in stationary camera sequences: background extraction followed by differencing and thresholding, and motion detection using optical flow field calculated by &ldquo<br>Kanade-Lucas Feature Tracker&rdquo<br>. For non-stationary camera sequences, different algorithms are developed based on the scen
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Toth, Levente. "3D object recognition based on constrained 2D views." Thesis, University of Plymouth, 1998. http://hdl.handle.net/10026.1/1808.

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The aim of the present work was to build a novel 3D object recognition system capable of classifying man-made and natural objects based on single 2D views. The approach to this problem has been one motivated by recent theories on biological vision and multiresolution analysis. The project's objectives were the implementation of a system that is able to deal with simple 3D scenes and constitutes an engineering solution to the problem of 3D object recognition, allowing the proposed recognition system to operate in a practically acceptable time frame. The developed system takes further the work o
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5

Govender, Natasha. "Active object recognition for 2D and 3D applications." Doctoral thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/16520.

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Includes bibliographical references<br>Active object recognition provides a mechanism for selecting informative viewpoints to complete recognition tasks as quickly and accurately as possible. One can manipulate the position of the camera or the object of interest to obtain more useful information. This approach can improve the computational efficiency of the recognition task by only processing viewpoints selected based on the amount of relevant information they contain. Active object recognition methods are based around how to select the next best viewpoint and the integration of the extracted
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6

Noé, Estelle. "3D layered articulated object from a single 2D drawing." Thesis, KTH, Medieteknik och interaktionsdesign, MID, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-216943.

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Modeling articulated objects made of rigid layered parts used to populate 3D scenes in video games or movie production is a complex and time-consuming task for digital artists. This work proposes a sketch-based approach to efficiently model 3D layered articulated objects, such as animals with rigid shells and armors, in annotating a single 2D photo manually, and eventually fabricate it from automatically computed 2D patterns. In considering symmetrical objects seen under a 3/4 view, and an- notating salient features such as extremities of the rigid articulated parts as a mix of circular and Be
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7

Zhu, Yonggen. "Feature extraction and 2D/3D object recognition using geometric invariants." Thesis, King's College London (University of London), 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.362731.

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8

Gamal, Eldin Ahmed. "Point process and graph cut applied to 2D and 3D object extraction." Nice, 2011. http://www.theses.fr/2011NICE4107.

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L’objectif de cette thèse est de développer une nouvelle approche de détection d’objets 3D à partir d’une image 2D, prenant en compte les occultations et les phénomènes de perspective. Cette approche est fondée sur la théorie des processus ponctuels marqués, qui a fait ses preuves dans la solution de plusieurs problèmes en imagerie haute résolution. Le travail de la thèse est structuré en deux parties. Dans la première partie, nous proposons une nouvelle méthode probabiliste pour gérer les occultations et les effets de perspective. Le modèle proposé est fondé sur la simulation d’une scène 3D u
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9

Gomez-Donoso, Francisco. "Contributions to 3D object recognition and 3D hand pose estimation using deep learning techniques." Doctoral thesis, Universidad de Alicante, 2020. http://hdl.handle.net/10045/110658.

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In this thesis, a study of two blooming fields in the artificial intelligence topic is carried out. The first part of the present document is about 3D object recognition methods. Object recognition in general is about providing the ability to understand what objects appears in the input data of an intelligent system. Any robot, from industrial robots to social robots, could benefit of such capability to improve its performance and carry out high level tasks. In fact, this topic has been largely studied and some object recognition methods present in the state of the art outperform humans in ter
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10

Sambra-Petre, Raluca-Diana. "2D/3D knowledge inference for intelligent access to enriched visual content." Phd thesis, Institut National des Télécommunications, 2013. http://tel.archives-ouvertes.fr/tel-00917972.

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This Ph.D. thesis tackles the issue of sill and video object categorization. The objective is to associate semantic labels to 2D objects present in natural images/videos. The principle of the proposed approach consists of exploiting categorized 3D model repositories in order to identify unknown 2D objects based on 2D/3D matching techniques. We propose here an object recognition framework, designed to work for real time applications. The similarity between classified 3D models and unknown 2D content is evaluated with the help of the 2D/3D description. A voting procedure is further employed in o
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