Sökning: "Person Re-Identification"
Visar resultat 1 - 5 av 11 uppsatser innehållade orden Person Re-Identification.
1. Enhancing person re-identification: leveraging DensePose for improving occlusion handling and generalization
Master-uppsats, Lunds universitet/Matematik LTHSammanfattning : In this master’s thesis we propose a DensePose-based person re-identification (re-ID) machine learning algorithm building upon previous research on this topic. DensePose, a deep neural network that performs human body part segmentation on images, forms the foundation of our approach. LÄS MER
2. Monitoring Activity Patterns In The Linnaean Botanical Gardens
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : The thesis aims at investigating and identifying people in two camera views as the same person and to establish communication, where two cameras will be placed in the different angle in Linnean Botanical Garden and the video is sent to the central station (PC). Then person-tracking and re-identification algorithms will be applied to track and identify whether it is the same person in the different camera views. LÄS MER
3. OSPREY: Person Re-Identification in the sport of Padel : Utilizing One-Shot Person Re-identification with locally aware transformers to improve tracking
Master-uppsats, Jönköping University/Jönköping AI Lab (JAIL)Sammanfattning : This thesis is concerned with the topic of person re-identification. Many tracking algorithms today cannot keep track of players reentering the scene from different angles and times. Therefore, in this thesis, current literature is explored to gather information about the topic, and a current state-of-the-art model is tested. LÄS MER
4. Pedestrian Multiple Object Tracking in Real-Time
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Multiple object tracking (MOT) is the task of detecting multiple objects in a scene and associating detections over time to form tracks. It is essential for many scene understanding tasks like surveillance, robotics and autonomous driving. LÄS MER
5. Pedestrian Tracking by using Deep Neural Networks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This project aims at using deep learning to solve the pedestrian tracking problem for Autonomous driving usage. The research area is in the domain of computer vision and deep learning. Multi-Object Tracking (MOT) aims at tracking multiple targets simultaneously in a video data. LÄS MER