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What is object detection problem?
Object detection is the problem of finding and classifying a variable number of objects on an image. In contrast with problems like classification, the output of object detection is variable in length, since the number of objects detected may change from image to image.
What is meant by object detection?
Definition. Object detection involves detecting instances of objects from a particular class in an image. Background. The goal of object detection is to detect all instances of objects from a known class, such as people, cars or faces in an image.
What is object detection Wikipedia?
Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos.
What is object detection in AI?
Object detection is an important computer vision task used to detect instances of visual objects of certain classes (for example, humans, animals, cars, or buildings) in digital images such as photos or video frames.
Why do we use object detection?
Object detection is a computer vision technique that allows us to identify and locate objects in an image or video. With this kind of identification and localization, object detection can be used to count objects in a scene and determine and track their precise locations, all while accurately labeling them.
What is the problem definition for object detection?
Problem Definition Object Detection ● Input: Image ● Output: multiple instances of ○ object location (bounding box) ○ object class 5 Problem Definition Object Detection ● Input: Image ● Output: multiple instances of ○ object location (bounding box) ○ object class
How is object detection used in artificial intelligence?
Problem Definition Object Detection ● Input: Image ● Output: multiple instances of ○ object location (bounding box) ○ object class Object class: ● Semantic class of the instance ○ Similar to object classification task, by predicting a vector of scores 8 Modern Object Detection Architecture (as of 2017)
How are bounding boxes used in object detection?
Bounding box: ● Rigid box that confines the instance ● Multiple possible parameterizations ○ (width, height, center x, center y) ○ (x1, y1, x2, y2) ○ (x1, y1, x2, y2, rotation) 7 Problem Definition Object Detection ● Input: Image ● Output: multiple instances of ○ object location (bounding box) ○ object class
How to use image classification for object detection?
Object Detection JunYoung Gwak 1 Motivation Image classification ● Input: Image ● Output: object class 2 Motivation Limitation of classification ● Multiple classes ● Location i.e. Object classification assumes ● Single class of object ● Occupies majority of the input image 3 Motivation We need high-level understanding of the complex world 4