Sökning: "Multi-Object tracking"

Visar resultat 1 - 5 av 13 uppsatser innehållade orden Multi-Object tracking.

1. 1. A Bidirectional ApproachApplied on Deeper and WiderSiamese Network

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Tobias Arnehall Johansson; [2023]
   Nyckelord :;

   Sammanfattning : Object tracking and object detection are two components within computer vision that have been widely improved during the last decade, in terms of precision and speed. This is mainly because deep learning has been incorporatedinto the algorithms, but also because new techniques and insights within the area are frequently released. LÄS MER

3. 2. 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

4. 3. Multi-Camera Multi-Person Tracking Using Reinforcement Learning

   Master-uppsats, Lunds universitet/Matematik LTH

   Författare :Axel Kärrholm; Linus Rickman; [2022]
   Nyckelord :Multi-Camera Multi-Object Tracking; Reinforcement Learning; Computer Vision; Machine Learning; Object Detection; Mathematics and Statistics;

   Sammanfattning : The problem of multi-object-tracking in a network of cameras is an interesting and non-trivial problem. Given videos from a number of cameras the goal of Multi-Camera Multi-Object Tracking (MCMOT) is to find the full visible trajectory of each pedestrian from the videos as the pedestrians move across cameras. LÄS MER

5. 4. Deep Learning for Multi-person Detection and Tracking in Mass Casualty Incidents

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

   Författare :Jakob Lindén; [2022]
   Nyckelord :;

   Sammanfattning : To evaluate and prioritize the injured during an incident of mass casualty, obtaining situational and positional awareness of the site is essential. There are situations where the first responders (nurses, firemen, police, etc.) cannot gain this perception by themselves. LÄS MER

7. 5. Point Cloud Data Augmentation for 4D Panoptic Segmentation

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

   Författare :Wangkang Jin; [2022]
   Nyckelord :Point Cloud; Data Augmentation; 4D panoptic segmentation; Deep Learning; 3D Perception; Autonomous Driving; Punktmoln; Dataökning; 4D panoptisk segmentering; Djup lärning; 3D Perception; 3D Uppfattning; Autonom körning;

   Sammanfattning : 4D panoptic segmentation is an emerging topic in the field of autonomous driving, which jointly tackles 3D semantic segmentation, 3D instance segmentation, and 3D multi-object tracking based on point cloud data. However, the difficulty of collection limits the size of existing point cloud datasets. LÄS MER