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Project Title: Using Computer Vision for Counting Things
Project Title: Using Computer Vision for Counting Things
Subhransu Maji co-directs the computer vision lab where he and his team of students aim to make fundamental contributions towards building AI systems with rich visual reasoning capabilities. The research focuses on architectures for visual recognition tasks, as well as techniques to improve their robustness, efficiency, generalization and interpretability. The team also engages in interdisciplinary research. In collaboration with ecologists we aim to analyze bird migration from radar imagery; with astronomers to uncover scientific insights from images of galaxies; as well as domain experts to develop applications in graphics, health care, material design, and sustainability.
Project Description:
Using computer vision and statistical estimation to solve counting in large image collections.
Counting in large image collections (e.g., how many cars passed a traffic sign, or how many animals live in a region) is challenging, and many modern applications use computer vision to detect and count objects in massive image collections. However, when the detection task is very difficult the counts may be inaccurate even with significant investments in training data and model development. The project will build on our ongoing work called DISCOUNT (Perez et al., AAAI 2024) on combining computer vision and human screening to obtain accurate counts. The students will learn about how computer vision can be used to classify images based on modern deep learning approaches, and evaluate statistical estimation approaches for estimating counts for some applications motivated by Ecology and other domains.
Learning Objectives:
Learn about modern computer vision tools for image classification based on deep learning
Develop a working knowledge on how to deploy these systems
Learn about statistical estimation techniques
Experiment and evaluate the performance of various approaches
Solve a large scale counting problem
Skills needed:
Programming: Python (especially numpy)
Math: Calculus, Probability
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