Essays about: "Discriminative Correlation Filters"

Showing result 1 - 5 of 6 essays containing the words Discriminative Correlation Filters.

1. 1. Tracking Under Countermeasures Using Infrared Imagery

   University essay from Linköpings universitet/Datorseende

   Author : Sara Modorato; [2022]
   Keywords : computer vision; infrared imagery; tracking; countermeasures; discriminative correlation filters; Efficient Convolution Operator tracker; Spatial-Temporal Regularized Correlation Filter tracker; Visual Object Tracking; flare; DIRCM; multiple wavelength bands; features;

   Abstract : Object tracking can be done in numerous ways, where the goal is to track a target through all frames in a sequence. The ground truth bounding box is used to initialize the object tracking algorithm. Object tracking can be carried out on infrared imagery suitable for military applications to execute tracking even without illumination. READ MORE

3. 2. Multi-Modal Visual Tracking Using Infrared Imagery

   University essay from Linköpings universitet/Datorseende

   Author : Emma Wettermark; Linda Berglund; [2021]
   Keywords : Visual object tracking; Discriminative correlation filters; Infrared imagery;

   Abstract : Generic visual object tracking is the task of tracking one or several objects in all frames in a video, knowing only the location and size of the target in the initial frame. Visual tracking can be carried out in both the infrared and the visual spectrum simultaneously, this is known as multi-modal tracking. READ MORE

4. 3. Visual Tracking Using Stereo Images

   University essay from Linköpings universitet/Datorseende

   Author : Carl Dehlin; [2019]
   Keywords : Visual Tracking; Stereo Vision; DCF; Discriminative Correlation Filters;

   Abstract : Visual tracking concerns the problem of following an arbitrary object in a video sequence. In this thesis, we examine how to use stereo images to extend existing visual tracking algorithms, which methods exists to obtain information from stereo images, and how the results change as the parameters to each tracker vary. READ MORE

5. 4. Incorporating Scene Depth in Discriminative Correlation Filters for Visual Tracking

   University essay from Linköpings universitet/Datorseende

   Author : John Stynsberg; [2018]
   Keywords : Tracking; Visual; Deep; Learning; Machine; Learning; CNN; Convolutional; Neural; Network; Unsupervised; Learning; 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; Filters; Normalized; Convolution; Bayesian; Gaussian; Mixture; Scale; Estimation; Conjugate; Gradient; Linkoping; Sweden; Visuell; Följning; Särdrag; Djupa; Faltningsnätverk; Maskininlärning; Djup; Inlärning; Genetiska; Algoritmer; Klustring; Djup; RGBD; Linköping; Sverige;

   Abstract : 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. READ MORE

6. 5. Visual Tracking with Deformable Continuous Convolution Operators

   University essay from Linköpings universitet/Datorseende

   Author : Joakim Johnander; [2017]
   Keywords : Visual Tracking; Discriminative Correlation Filters; DCF; Deformable Filters; Computer Vision; Filter Optimization;

   Abstract : Visual Object Tracking is the computer vision problem of estimating a target trajectory in a video given only its initial state. A visual tracker often acts as a component in the intelligent vision systems seen in for instance surveillance, autonomous vehicles or robots, and unmanned aerial vehicles. READ MORE