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PROGRESS PRESENTATION

Assignment 0X (dd/mm/yyyy) JohnSmith, JohnSmith, JohnSmith, JohnSmith, JohnSmith. PROGRESS PRESENTATION. Assignment description. Color Depolarization of super-pixel artifacts Multifiltering of spectral Gaussians Decoloration of traffic lipids.

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PROGRESS PRESENTATION

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  1. Assignment 0X (dd/mm/yyyy) JohnSmith, JohnSmith, JohnSmith, JohnSmith, JohnSmith. PROGRESS PRESENTATION Assignment description • Color Depolarization of super-pixel artifacts • Multifiltering of spectral Gaussians • Decoloration of traffic lipids Master in Computer Vision and Artificial Intelligence mcvai.uab.es Computer Vision Center and Institut d’Investigació en Ingel·ligencia Artificial (Universitat Autònoma de Barcelona)

  2. Assignment 0X (dd/mm/yyyy) JohnSmith, JohnSmith, JohnSmith, JohnSmith, JohnSmith. PROGRESS PRESENTATION Exercise 1. Implementation • init_models1.m • kalman_filter.m Matlab Code Matlab Code Master in Computer Vision and Artificial Intelligence mcvai.uab.es Computer Vision Center and Institut d’Investigació en Ingel·ligencia Artificial (Universitat Autònoma de Barcelona)

  3. Assignment 0X (dd/mm/yyyy) JohnSmith, JohnSmith, JohnSmith, JohnSmith, JohnSmith. PROGRESS PRESENTATION Exercise 2. Models • Compare the trajectories obtained with the models in InitModels2a and InitModels2b. How can you explain the abruptness or smoothness of each trajectory, in terms of the model used? Master in Computer Vision and Artificial Intelligence mcvai.uab.es Computer Vision Center and Institut d’Investigació en Ingel·ligencia Artificial (Universitat Autònoma de Barcelona)

  4. Assignment 0X (dd/mm/yyyy) JohnSmith, JohnSmith, JohnSmith, JohnSmith, JohnSmith. PROGRESS PRESENTATION Exercise 3. Performance (Seq2.avi) • Compare the trajectories obtained with the models in InitModels2a and InitModels2b. How can you explain the abruptness or smoothness of each trajectory, in terms of the model used? Master in Computer Vision and Artificial Intelligence mcvai.uab.es Computer Vision Center and Institut d’Investigació en Ingel·ligencia Artificial (Universitat Autònoma de Barcelona)

  5. Assignment 0X (dd/mm/yyyy) JohnSmith, JohnSmith, JohnSmith, JohnSmith, JohnSmith. PROGRESS PRESENTATION Exercise 4. Gating (Seq2_miss.avi) • Is the target misstracked ? Why? • Modify data_association.m and kalman_filter.m according to assignment instructions. • Does it solves the problem ? How the Kalman estimation behaves in the abscense of observations ? Matlab Code Master in Computer Vision and Artificial Intelligence mcvai.uab.es Computer Vision Center and Institut d’Investigació en Ingel·ligencia Artificial (Universitat Autònoma de Barcelona)

  6. Assignment 0X (dd/mm/yyyy) JohnSmith, JohnSmith, JohnSmith, JohnSmith, JohnSmith. PROGRESS PRESENTATION Optional Exercise. EKF or UKF (Seq3.avi) • Details of the implementation, performance analysis, ... Master in Computer Vision and Artificial Intelligence mcvai.uab.es Computer Vision Center and Institut d’Investigació en Ingel·ligencia Artificial (Universitat Autònoma de Barcelona)

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