Student Competition: Computer Vision Training, Object Detection: Part 1

Learn to detect objects using binary classifiers; template matching, histogram of gradients (HOG), and cascade object detection.

You’ll learn  how Template Matching works and how to use it. The concepts behind HOG will be taught to prepare you for the Cascade Object Detector. The Cascade Object Detector is a robust detector which provides the option to use Haar, Local Binary Patterns (LBP), and HOG to detect objects within an image.

Template Matching and Cascade Object Detection are used to detect objects in an image that are aspect ratio and orientation invariant. Template Matching has an additional limitation that the object must be scale invariant. Both methods are useful for determining if an object is located within an image, and if so, where the object is located within the image.

Additional Information:

• Why Train a Cascade Object Detector?
• What Kinds of Objects Can You Detect with a Cascade Object Detector?
• How Does the Cascade Classifier Work?
• How to Create a Cascade Classifier Using the trainCascadeObjectDetector?
• Troubleshooting Cascade Object Detector Training
• extractHOGFeatures function documentation
• Label Images for Classification Model Training
• trainCascadeObjectDetector function documentation