Which method of segmentation fits better to this overlap problem?
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I am currently working on the monitoring of cows with the help of a thermal video, for this I first do a segmentation based on distance transformation (it is the best I have found).
Later for the follow-up I am using a combination of local descriptors and kalman filters.
Additionally the video is very low resolution 160x120 from a flir camera.
But with all these tools it is difficult for me to solve overlap situations. That is why I ask if anyone knows any better segmentation than the one I am currently using, or some method to better follow my objects of interest.
(photos attached)
Original Image:
Segmentation Image:
Original Image 2:
Segmentation Image2:
Tracked Objects:
opencv image-processing image-segmentation video-tracking flir
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up vote
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I am currently working on the monitoring of cows with the help of a thermal video, for this I first do a segmentation based on distance transformation (it is the best I have found).
Later for the follow-up I am using a combination of local descriptors and kalman filters.
Additionally the video is very low resolution 160x120 from a flir camera.
But with all these tools it is difficult for me to solve overlap situations. That is why I ask if anyone knows any better segmentation than the one I am currently using, or some method to better follow my objects of interest.
(photos attached)
Original Image:
Segmentation Image:
Original Image 2:
Segmentation Image2:
Tracked Objects:
opencv image-processing image-segmentation video-tracking flir
add a comment |
up vote
1
down vote
favorite
up vote
1
down vote
favorite
I am currently working on the monitoring of cows with the help of a thermal video, for this I first do a segmentation based on distance transformation (it is the best I have found).
Later for the follow-up I am using a combination of local descriptors and kalman filters.
Additionally the video is very low resolution 160x120 from a flir camera.
But with all these tools it is difficult for me to solve overlap situations. That is why I ask if anyone knows any better segmentation than the one I am currently using, or some method to better follow my objects of interest.
(photos attached)
Original Image:
Segmentation Image:
Original Image 2:
Segmentation Image2:
Tracked Objects:
opencv image-processing image-segmentation video-tracking flir
I am currently working on the monitoring of cows with the help of a thermal video, for this I first do a segmentation based on distance transformation (it is the best I have found).
Later for the follow-up I am using a combination of local descriptors and kalman filters.
Additionally the video is very low resolution 160x120 from a flir camera.
But with all these tools it is difficult for me to solve overlap situations. That is why I ask if anyone knows any better segmentation than the one I am currently using, or some method to better follow my objects of interest.
(photos attached)
Original Image:
Segmentation Image:
Original Image 2:
Segmentation Image2:
Tracked Objects:
opencv image-processing image-segmentation video-tracking flir
opencv image-processing image-segmentation video-tracking flir
edited Nov 11 at 8:25
Shai
68.4k22134238
68.4k22134238
asked Nov 8 at 22:08
Daniel Andres
61
61
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