Object Detection

本文介绍了目标检测领域的几个核心概念和技术,包括物体分类、定位、地标检测等,并详细阐述了滑动窗口检测算法及其卷积实现方式,以及YOLO算法的工作原理和非极大值抑制的应用。

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Concepts

NameDescriptionyy
Object Classification At most one object y=(c1c2c3)
Object LocalizationAt most one objecty=pcbxbybwbhc1c2c3y=(pcbxbybwbhc1c2c3)
Landmark DetectionAt most one objecty=pcl1xl1yl64xl64yy=(pcl1xl1y⋮l64xl64y)
Object DetectionMultiple objects

Sliding Windows Object Detection Algorithm

  1. Input: closely cropped images by sliding window
  2. Crop images with larger window

Disadvantage

Complex computation

Convolutional Implement of Sliding Windows

Turn Full Connection (FC) into convolutional layer

Bounding Box Detection

Yolo (You only look once) Algorithm
IoU (Intersection over Union)

Non-max Supression (NMS)

Discard all boxes with low pcpc
While remaining boxes exists:
1. Pick the box with the largest pcpc , output that as a prediction
2. Discard remaining boxes with IoU 0.5≥0.5 with the box output in previous step

Region Proposal

R-RNN: Segmentation Algorithm
Fast R-RNN
Faster R-RNN

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