Sökning: "mobile object detection"

Visar resultat 1 - 5 av 37 uppsatser innehållade orden mobile object detection.

1. 1. Smart Tracking for Edge-assisted Object Detection : Deep Reinforcement Learning for Multi-objective Optimization of Tracking-based Detection Process

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Shihang Zhou; [2023]
   Nyckelord :Tracking-By-Detection; Deep Reinforcement Learning; Multi-Objective Optimization; Spårning genom detektion; Djup förstärkningsinlärning; Multiobjektiv optimering;

   Sammanfattning : Detecting generic objects is one important sensing task for applications that need to understand the environment, for example eXtended Reality (XR), drone navigation etc. However, Object Detection algorithms are particularly computationally heavy for real-time video analysis on resource-constrained mobile devices. LÄS MER

3. 2. Robust Multi-Modal Fusion for 3D Object Detection : Using multiple sensors of different types to robustly detect, classify, and position objects in three dimensions.

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Viktor Kårefjärd; [2023]
   Nyckelord :Computer Vision; 3D Object Detection; Multi-Modal Fusion; Deep Learning; Datorseenden; 3D-objektdetektion; Multimodal fusion; Djupinlärning;

   Sammanfattning : The computer vision task of 3D object detection is fundamentally necessary for autonomous driving perception systems. These vehicles typically feature a multitude of sensors, such as cameras, radars, and light detection and ranging sensors. LÄS MER

4. 3. Probabilistic Multi-Modal Data Fusion and Precision Coordination for Autonomous Mobile Systems Navigation : A Predictive and Collaborative Approach to Visual-Inertial Odometry in Distributed Sensor Networks using Edge Nodes

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Isabella Luppi; [2023]
   Nyckelord :Distributed Sensor Networks; Point Cloud Processing; Bounding Box Fitting; Trajectory Tracking; Distributed Estimation; Predictive Estimation; Edge-Computing; Reti di Sensori Distribuiti; Elaborazione di Nuvole di Punti; Riquadri di Delimitazione; Tracciamento della Traiettoria; Stima Distribuita; Stima Predittiva; Calcolo Distribuito.; Distribuerade Sensornätverk; Bearbetning av Punktmoln; Anpassning av Begränsningsruta; Trajektorieuppföljning; Distribuerad Uppskattning; Prediktiv Uppskattning; Edge-datorbehandling;

   Sammanfattning : This research proposes a novel approach for improving autonomous mobile system navigation in dynamic and potentially occluded environments. The research introduces a tracking framework that combines data from stationary sensing units and on-board sensors, addressing challenges of computational efficiency, reliability, and scalability. LÄS MER

5. 4. Unsupervised Domain Adaptation for 3D Object Detection Using Adversarial Adaptation : Learning Transferable LiDAR Features for a Delivery Robot

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Mattias Hansson; [2023]
   Nyckelord :Unsupervised Domain Adaptation; 3D Object Detection; Mobile Robotics; Adversarial Adaptation; Computer Vision; Oövervakad Domänanpassning; 3D Objektigenkänning; Mobila Robotar; Motspelaranpassning; Datorseende;

   Sammanfattning : 3D object detection is the task of detecting the full 3D pose of objects relative to an autonomous platform. It is an important perception system that can be used to plan actions according to the behavior of other dynamic objects in an environment. LÄS MER

7. 5. Automatic object detection and tracking for eye-tracking analysis

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

   Författare :Liv Cederin; Ulrika Bremberg; [2023]
   Nyckelord :Computer Vision; Object Detection; Object Tracking; Eye-Tracking; Annotation; Deblurring; Deep Learning; Motion Blur;

   Sammanfattning : In recent years, eye-tracking technology has gained considerable attention, facilitating analysis of gaze behavior and human visual attention. However, eye-tracking analysis often requires manual annotation on the objects being gazed upon, making quantitative data analysis a difficult and time-consuming process. LÄS MER