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1
Intro
2
Sliding Window
3
Sliding Window Approach
4
Scale Space Parameter
5
Question
6
Motivation
7
Pyramid Construction
8
Aspect Ratio
9
Feature Extraction
10
Classification
11
Postprocessing
12
Question from Fatima
13
Post Processing
14
Edge Detection
15
Intersection Over Union
16
Other Terms
17
Precision Recall
18
Compute Map
Description:
Explore object detection techniques in this comprehensive computer vision lecture. Delve into sliding window approaches, scale space parameters, and pyramid construction for efficient object localization. Learn about aspect ratio considerations, feature extraction methods, and classification strategies. Understand postprocessing techniques, including edge detection and intersection over union. Examine precision-recall metrics and mean average precision (mAP) computation for evaluating object detection performance. Gain valuable insights into the fundamental concepts and advanced algorithms used in modern object detection systems.

Object Detection Techniques - Part I - Lecture 20

University of Central Florida
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