object detection - OpenGenus IQ: Learn Algorithms, DL, System Design

Using Histogram of Oriented Gradients (HOG) for Object Detection

Principle behind histogram of oriented gradients is that local object appearance and shape within an image can be described by the distribution of intensity gradients or edge directions and hence, can be used for object detection

Machine Learning (ML)

Learn about various Object Detection Techniques

We will understand what is object detection, why we need to do object detection and the basic idea behind various techniques used to solved this problem. We start with the basic techniques like Viola Jones face detector to some of the advanced techniques like Single Shot Detector.

Machine Learning (ML)

You only look once (YOLO) algorithm

You only look once (YOLO) is a state-of-the-art, real-time object detection system. It is a fully convolutional network. On a Pascal Titan X, it processes images at 30 FPS and has a mAP of 57.9% on COCO. It has 75 convolutional layers with skip connections and upsampling layers and no pooling.

Machine Learning (ML)

Single Shot Detection (SSD) Algorithm

Single Shot MultiBox Detector (SSD) is an object detection algorithm that is a modification of the VGG16 architecture. It reached new records in terms of performance and precision for object detection tasks, scoring over 74% mAP at 59 frames per second on standard datasets such as PascalVOC and COCO

Machine Learning (ML)

Overview of Object Detection in Computer Vision

Object detection models are used to identify multiple relevant objects in a single image.The second significant advantage of object detection models versus image classification ones is that location of the objects is provided. Popular Object Detection Models are YOLO and SSD.