*My post explains Keypoint Detection(Landmark Detection), Image Matching, Object Tracking, Stereo Matching, Video Prediction, Optical Flow, Image Captioning.
Computer Vision is the technology which enables a computer to understand and analyze the visual things such as images, videos, etc.
There are many Computer Vision technologies as shown below:
(1) Image Classification(Recognition):
- can classify an entire image into one or more classes(labels) from one or more classes(labels):
*Memos:
- The image can be one frame in a video.
- There is also Video Classification to classify an entire video into one or more classes(labels) from one or more classes(labels).
- has the method Single-Label Classification which has two methods Binary Classification and Multi-Class Classification.
- has the method Multi-Label Classification.
*Memos:
- Binary Classification can classify an entire image into a single class(label) from two classes(labels).
- Multi-Class Classification can classify an entire image into a single class(label) from more than two classes(labels).
- Multi-Label Classification can classify an entire image into multiple classes(labels) from more than two classes(labels).
(2) Object Localization:
- can localize the objects and interest regions in an image with bounding boxes. *The image can be one frame in a video.
(3) Object Detection:
- can localize and classify the objects and interest regions in an image with classes(labels) and bounding boxes. *The image can be one frame in a video.
- is the combination of Object Localization and Image Classification(Recognition).
- used for Object Tracking.
(4) Image Segmentation:
- can do Object Detection more precisely, differentiating stuff and things with colors:
*Memos:
- Stuff is uncountable things(classes) such as sky, sea, forrest, road, grass, landscape, etc.
- Things are countable things(classes) such as car, tree, person, animal, flower, etc.
- has the popular methods Semantic Segmentation, Instance Segmentation and Panoptic segmentation:
*Memos:
- Semantic Segmentation is good at differentiating stuff but not good at differentiating things.
- Instance Segmentation is good at differentiating things but not good at differentiating stuff.
- Panoptic segmentation:
- is good at differentiating both stuff and things.
- is the combination of Semantic Segmentation and Instance Segmentation.
- is used for Medical Imaging(CT scans, MRIs, X-rays, etc), Autonomous Vehicles, Satellite Imagery, Agriculture, Robotics, Surveillance, Industrial Inspection, Face Recognition, etc.
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