Detección de objetos

Explore the foundational concepts of object detection, including image formation, pixel characteristics, and template matching. Gain an understanding of different methods for image representation and classification, setting the stage for the subsequent modules.

Dive into the world of image classification with a focus on Local Binary Patterns, Histogram LBP, and Regression Logistic. Explore the intricacies of these methods and their application in classifying objects within images.

Delve into the specifics of object detection, covering topics such as candidate generation, evaluation of classification by window, and training and validation sets. Gain practical experience through example code and proposed exercises.

Uncover the complexities of building a detector based on HOG/SVM, including the calculation of gradients, histograms, and the fundamental concepts of Support Vector Machines. Test and enhance your knowledge with example code and supplementary materials.

Learn about building a detector based on Haar/Adaboost, covering integral images, Adaboost, and the implementation details of a cascaded classifier. Strengthen your understanding with additional materials and self-assessment exercises.

Explore advanced techniques such as DPM models, domain adaptation, Convolutional Neural Networks, and various image modalities. Gain a comprehensive understanding of cutting-edge methods for object detection and recognition.