Incorporating Scene Depth in Discriminative Correlation Filters for Visual Tracking

Incorporating Scene Depth in Discriminative Correlation Filters for Visual Tracking

Visual tracking is a computer vision problem where the task is to follow a targetthrough a video sequence. Tracking has many important real-world applications in several fields such as autonomous vehicles and robot-vision. Since visual tracking does not assume any prior knowledge about the target, i...

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Bibliographic Details
Main Author: Stynsberg, John
Format: Others
Language:English
Published: Linköpings universitet, Datorseende 2018
Subjects:
Tracking
Visual
Deep
Learning
Machine
CNN
Convolutional
Neural
Network
Unsupervised
Clustering
Genetic Algorithms
Features
Visual featues
Channel
Coding
RGBD
Scene
Depth
Map
Kinect
Discriminative
Correlation
Filters
SRDCF
DCF
Spatial
Spatially
Regularized
Hyperparameter
Search
Occlusion
Detection
Handling
Kalman
Normalized
Convolution
Bayesian
Gaussian
Mixture
Scale
Estimation
Conjugate
Gradient
Linkoping
Sweden
Visuell
Följning
Särdrag
Djupa
Faltningsnätverk
Maskininlärning
Djup
Inlärning
Genetiska
Algoritmer
Klustring
Linköping
Sverige
Computer Vision and Robotics (Autonomous Systems)
Datorseende och robotik (autonoma system)
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153110

Internet

http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-153110

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