Image processing and computer vision Chapter 7 Mean-shift and cam-shift Ref o[1] Dorin Comaniciu, Peter Meer, "Mean Shift: A Robust Approach Toward Feature Space Analysis"Volume 24, Issue 5(May 2002),IEEE Transactions on Pattern Analysis and Machine Intelligence e[2]web. missouri. edu/hantx/ECE8001/notes/Lect7 mean shift. pdf Camshift vod
Image processing and computer vision Chapter 7: Mean-shift and Cam-shift Ref ⚫[1] Dorin Comaniciu, Peter Meer,"Mean Shift: A Robust Approach Toward Feature Space Analysis"Volume 24 , Issue 5 (May 2002),IEEE Transactions on Pattern Analysis and Machine Intelligence ⚫[2] web.missouri.edu/~hantx/ECE8001/notes/Lect7_mean_shift.pdf Camshift v9d 1
INtroduction Kernel density I Kernel choices I Peak finding I Mean-shift 1 Cam-shift What is Mean-shift? Find the peak of a probability function by the change of the mean of the data Applications Non-rigid object tracking Segmentation Camshift vod
Introduction | Kernel density | Kernel choices | Peak finding | Mean-shift | Cam-shift What is Mean-shift? • Find the peak of a probability function by the change of the mean of the data • Applications: – Non-rigid object tracking – Segmentation Camshift v9d 2
INtroduction Kernel density I Kernel choices I Peak finding I Mean-shift 1 Cam-shift Applications: segmentation of regions of images in a movie Use color to segment the image into logical regions for analysIS. If the regions are moving, mean-shift is useful Camshift vod .https://www.youtube.com/watch?v=rdtun7a6h08
Introduction | Kernel density | Kernel choices | Peak finding | Mean-shift | Cam-shift Applications: segmentation of regions of images in a movie • Use color to segment the image into logical regions for analysis. • If the regions are moving , mean-shift is useful. Camshift v9d 3 •https://www.youtube.com/watch?v=rDTun7A6HO8
INtroduction Kernel density I Kernel choices I Peak finding I Mean-shift 1 Cam-shift Application: tracking non-rigid object Human tracking http.://ww.youtube.com/watch?v=zltjpfpp9hy Camshift vod
Introduction | Kernel density | Kernel choices | Peak finding | Mean-shift | Cam-shift Application: tracking non-rigid object • Human tracking Camshift v9d 4 http://www.youtube.com/watch?v=zLtjPfPP9HY
INtroduction Kernel density I Kernel choices I Peak finding I Mean-shift 1 Cam-shift Intuition: find the mode by mean shift Target: Find the modes (peaks) in a set of sample data The mode of a continuous probability distribution is the peak. There may be multiple peaks The method used is called mean -shift MIX By finding the shift of the mean, we can find the tp mode (peak) It can be used to segment an image into logical regions.e.g. within each region, the color is the same) Camshift vod 5
Introduction | Kernel density | Kernel choices | Peak finding | Mean-shift | Cam-shift Intuition: find the mode by mean-shift • Target : Find the modes (peaks) in a set of sample data. – The mode of a continuous probability distribution is the peak. – There may be multiple peaks. • The method used is called mean-shift. – By finding the shift of the mean, we can find the mode (peak) • It can be used to segment an image into logical regions. (e.g. within each region, the color is the same.) Camshift v9d 5