10 Popular Computer Vision Projects for Beginners

10 Popular Computer Vision Projects for Beginners

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10 Popular Computer Vision Projects for Beginners

One of the most challenging topics in artificial intelligence is computer vision technology. In recent years, with the increasing application of computer vision, this technology has been widely used in fields such as robotics, surveillance, and healthcare.
In this article, we list ten popular computer vision projects along with their available datasets for beginners to learn:
1. Color Detection
In this project, the model’s goal is to detect every color in an image. A popular color detection project uses OpenCV’s invisibility cloak.
Dataset: Google-512 Dataset
Link: https://cvhci.anthropomatik.kit.edu/~bschauer/datasets/google-512/
2. Edge Detection
Edge detection is an image processing technique used to detect edges in an image to determine the boundaries of objects. This technique identifies edges by detecting discontinuities in brightness. Common edge detection algorithms include Canny, fuzzy logic methods, etc.
Dataset: USC-SIPI Image Database
Link: http://sipi.usc.edu/database/
3. Face Detection
In this project, the model’s goal is to detect human faces by mapping facial features in videos or images. These projects involve multiple steps, such as mapping features, using Principal Component Analysis (PCA), matching data with a database, etc.
Dataset: IMDB Wiki Dataset
Link: https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/
4. Gesture Recognition
Gesture recognition is one of the key topics in human-computer interaction. This project requires several tasks, including extracting the hand region from the background and segmenting the palm and fingers to detect finger movements. Applications of gesture recognition can be found in virtual reality games, sign language, etc.
Dataset: Microsoft Kinect and Leap Motion Dataset
Link: https://lttm.dei.unipd.it/downloads/gesture/
5. People Counting
The goal of this project is to count the number of people passing through a specific scene. Applications of this project include civilian surveillance, pedestrian tracking, and counting.
Dataset: People Counting Dataset (PCDS)
Link: https://github.com/shijieS/people-counting-dataset
6. Image Segmentation
Image segmentation is an essential technique in image processing. This technique can be used in computer graphics, object synthesis, etc. The goal of this project is to design, implement, and test on multiple regions of a set of images based on segmentation algorithms.
Dataset: Berkeley Segmentation Dataset and Benchmark
Link: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/
7. Image Classification
The goal of this project is to classify images that define a set of target categories. This is a supervised learning problem where the model is trained to identify categories using labeled images.
Dataset: CIFAR-10 Dataset
Link: http://www.cs.toronto.edu/~kriz/cifar.html
8. Image Colorization
Image colorization is a technique for adding style to photos or applying various methods to photos. A popular image colorization project uses OpenCV to convert black and white images. The goal of this project is to generate output color images representing semantic colors and tones by taking input grayscale images.
Dataset: Image Colorization Dataset
Link: https://www.kaggle.com/shravankumar9892/image-colorization
9. Object Tracking
The goal of this project is to develop an object tracking system in constrained environments. This includes detecting objects from the background and tracking their positions. Object tracking consists of two parts – prediction and correction. The system predicts the next state of the object based on its current state and corrects that state based on the true state.
Dataset: Tracking Long and Prosper–TLP Dataset
Link: https://amoudgl.github.io/tlp/
10. Vehicle Counting
The goal of this project is to count vehicles with very good accuracy even in challenging scenes related to occlusion and/or shadows. The vehicle counting project can be used for traffic monitoring.
Dataset: Vehicle Image Dataset
Link: https://www.gti.ssr.upm.es/data/Vehicle_database.html
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