Relevant bibliographies by topics / Robust Human Detection

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  1. Dissertations / Theses

Academic literature on the topic 'Robust Human Detection'

Author: Grafiati
Published: 11 September 2023

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Dissertations / Theses on the topic "Robust Human Detection"

1

Li, Ying. "Efficient and Robust Video Understanding for Human-robot Interaction and Detection." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu152207324664654.

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Leu, Adrian [Verfasser]. "Robust Real-time Vision-based Human Detection and Tracking / Adrian Leu." Aachen : Shaker, 2014. http://d-nb.info/1060622432/34.

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Leu, Adrian [Verfasser], Axel [Akademischer Betreuer] Gräser, and Udo [Akademischer Betreuer] Frese. "Robust Real-time Vision-based Human Detection and Tracking / Adrian Leu. Gutachter: Udo Frese. Betreuer: Axel Gräser." Bremen : Staats- und Universitätsbibliothek Bremen, 2014. http://d-nb.info/1072226340/34.

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Terzi, Matteo. "Learning interpretable representations for classification, anomaly detection, human gesture and action recognition." Doctoral thesis, Università degli studi di Padova, 2019. http://hdl.handle.net/11577/3423183.

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The goal of this thesis is to provide algorithms and models for classification, gesture recognition and anomaly detection with a partial focus on human activity. In applications where humans are involved, it is of paramount importance to provide robust and understandable algorithms and models. A way to accomplish this requirement is to use relatively simple and robust approaches, especially when devices are resource-constrained. The second approach, when a large amount of data is present, is to adopt complex algorithms and models and make them robust and interpretable from a human-like point
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Zhu, Youding. "Model-Based Human Pose Estimation with Spatio-Temporal Inferencing." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1242752509.

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Tasaki, Tsuyoshi. "People Detection based on Points Tracked by an Omnidirectional Camera and Interaction Distance for Service Robots System." 京都大学 (Kyoto University), 2013. http://hdl.handle.net/2433/180473.

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7

Yi, Fei. "Robust eye coding mechanisms in humans during face detection." Thesis, University of Glasgow, 2018. http://theses.gla.ac.uk/31011/.

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We can detect faces more rapidly and efficiently compared to non-face object categories (Bell et al., 2008; Crouzet, 2011), even when only partial information is visible (Tang et al., 2014). Face inversion impairs our ability to recognise faces. The key to understand this effect is to determine what special face features are processed and how coding of these features is affected by face inversion. Previous studies from our lab showed coding of the contralateral eye in an upright face detection task, which was maximal around the N170 recorded at posterior-lateral electrodes (Ince et al., 2016b;
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Alanenpää, Madelene. "Gaze detection in human-robot interaction." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-428387.

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The aim of this thesis is to track gaze direction in a human-robot interaction scenario.The human-robot interaction consisted of a participant playing a geographic gamewith three important objects on which participants could focus: A tablet, a sharedtouchscreen, and a robot (called Furhat). During the game, the participant wasequipped with eye-tracking glasses. These collected a first-person view video as wellas annotations consisting of the participant's center of gaze. In this thesis, I aim to usethis data to detect the three important objects described above from the first-personvideo strea
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Antonucci, Alessandro. "Socially aware robot navigation." Doctoral thesis, Università degli studi di Trento, 2022. https://hdl.handle.net/11572/356142.

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A growing number of applications involving autonomous mobile robots will require their navigation across environments in which spaces are shared with humans. In those situations, the robot’s actions are socially acceptable if they reflect the behaviours that humans would generate in similar conditions. Therefore, the robot must perceive people in the environment and correctly react based on their actions and relevance to its mission. In order to give a push forward to human-robot interaction, the proposed research is focused on efficient robot motion algorithms, covering all the tasks needed i
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Briquet-Kerestedjian, Nolwenn. "Impact detection and classification for safe physical Human-Robot Interaction under uncertainties." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC038/document.

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La problématique traitée dans cette thèse vise à développer une stratégie efficace de détection et de classification des impacts en présence d'incertitudes de modélisation du robot et de son environnement et en utilisant un nombre minimal de capteurs, notamment en l'absence de capteur d’effort.La première partie de la thèse porte sur la détection d'un impact pouvant avoir lieu à n'importe quel endroit du bras robotique et à n'importe quel moment de sa trajectoire. Les méthodes de détection d’impacts sont généralement basées sur un modèle dynamique du système, ce qui les rend sujettes au compro
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