Sökning: "object localization"

Visar resultat 1 - 5 av 63 uppsatser innehållade orden object localization.

  1. 1. Automatic Semantic Segmentation of Indoor Datasets

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Sai Swaroop Rachakonda; [2024]
    Nyckelord :Semantic Segmentation; Annotation; SLAM; Indoor datasets; YOLO V8; DETIC; Segment Anything Model.;

    Sammanfattning : Background: In recent years, computer vision has undergone significant advancements, revolutionizing fields such as robotics, augmented reality, and autonomoussystems. Key to this transformation is Simultaneous Localization and Mapping(SLAM), a fundamental technology that allows machines to navigate and interactintelligently with their surroundings. LÄS MER

  3. 2. Dynamic Object Removal for Point Cloud Map Creation in Autonomous Driving : Enhancing Map Accuracy via Two-Stage Offline Model

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

    Författare :Weikai Zhou; [2023]
    Nyckelord :Autonomous driving; Dynamic object removal; Map creation; 3D point cloud; Autonom körning; Dynamiska objekt borttagning; Skapande av kartor; 3D-punktmoln;

    Sammanfattning : Autonomous driving is an emerging area that has been receiving an increasing amount of interest from different companies and researchers. 3D point cloud map is a significant foundation of autonomous driving as it provides essential information for localization and environment perception. LÄS MER

  4. 3. Object Recognition and Tracking of Bolts: A Comparative Analysis of CNN Models and Computer Vision Techniques : A Comparison of CNN Models and Tracking Algorithms

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

    Författare :Serhat Bulun; [2023]
    Nyckelord :;

    Sammanfattning : The newer generation industry 4.0 focuses on development of both flexibility and autonomy for power tools used by companies in different mechanical areas and assembly lines. One area for automation is the application of computer vision in power tools to detect, identify and track bolts. LÄS MER

  5. 4. Image-Guided Zero-Shot Object Detection in Video Games : Using Images as Prompts for Detection of Unseen 2D Icons

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

    Författare :Axel Larsson; [2023]
    Nyckelord :Computer Vision; Deep learning; Machine learning; Object detection; Zeroshot; Datorseende; Djupinlärning; Maskininlärning; Objektdetektering; Zero-shot;

    Sammanfattning : Object detection deals with localization and classification of objects in images, where the task is to propose bounding boxes and predict their respective classes. Challenges in object detection include large-scale annotated datasets and re-training of models for specific tasks. LÄS MER

  7. 5. Analyzing different approaches to Visual SLAM in dynamic environments : A comparative study with focus on strengths and weaknesses

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

    Författare :Kristín Sól Ólafsdóttir; [2023]
    Nyckelord :Visual SLAM; RGB-D Vision; Dynamic Objects; Object Detection; Multi-Object Tracking; Image Segmentation; Optical Flow; Visual SLAM; RGB-D Syn; Dynamiska objekt; Objektdetektering; Multi-Objekt Spårning; Bildsegmentation; Optiskt Flöde;

    Sammanfattning : Simultaneous Localization and Mapping (SLAM) is the crucial ability for many autonomous systems to operate in unknown environments. In recent years SLAM development has focused on achieving robustness regarding the challenges the field still faces e.g. dynamic environments. LÄS MER