Concept

Computer stereo vision

Related lectures (32)

Geometric Stereo: Depth Recovery Techniques

Discusses geometric stereo principles and depth recovery techniques using stereo vision methods.

Explores geometric stereo, epipolar geometry, correlation methods, occlusions, and real-time implementation challenges in stereo vision systems.

Shape From Stereo-2

Explores stereo vision concepts such as occlusions, window size impact, multi-view stereo, dynamic shape reconstruction, and graph-based segmentation.

Synthetic Training Data via Generative Models

Explores the benefits of synthetic data in computer vision through generative models mimicking real images with low sim2real gap.

Course Project Choice

Introduces the course project for CS-503, emphasizing the importance of project selection related to vision and perceptual agents.

Delineation: Techniques and Dynamics

Explores techniques for delineating objects in images, including dynamic programming and live wire methods.

Visual Intelligence: Machines and Minds

Explores the history and techniques of computer vision, covering image formation, transformation, dynamic perspectives, and 3D estimation cues.

Shape from Shading: Recovering 3D Information from 2D Images

Covers the techniques for recovering 3D shape information from 2D images using shading models and modern deep learning approaches.

Edge Detection: Deep Learning Insights

Explores the evolution of edge detection techniques, from Canny to deep learning insights.

Shape from Contours

Explores shape reconstruction from contours using edge-based stereo matching and visual hull techniques for accurate 3D reconstruction.

Visual Intelligence: Projects and Challenges

Explores projects and challenges in visual intelligence, including hands-on learning and analysis of vision methods.

Machine Learning for Feature Extraction

Explores machine learning for feature extraction, 3D vision, and neural networks in mobile robotics.

Internship Report: Hangqian Li

Covers an internship report at Tencent Al lab, focusing on 3D avatar reconstruction and neural rendering techniques.

Depth Perception: Monocular and Binocular Cues

Covers depth perception, focusing on monocular and binocular cues, including motion parallax and stereoscopic vision.

Thermal Comfort Monitoring: Non-Intrusive Solutions

Presents a framework for non-intrusive thermal comfort monitoring using computer vision and machine learning techniques.

Visual Intelligence: Machines and Minds

Explores visual intelligence, covering image formation, perception, computer vision, correspondence learning, motion analysis, and recognition in videos.

Robust Vision: Data Augmentation and Ensembling Techniques

Explores data augmentation and ensembling techniques for robust vision, comparing ViT and ResNet models.

Computer Vision: Recap

Recaps key concepts in computer vision, challenges, opportunities, and upcoming exam details.

Social Media Images: Understanding Food Perception with Deep Learning

Explores deep learning with Instagram images, understanding food perception, obesity, and mental health, and discusses the impact of social media images and ephemeral platforms like Snapchat.

Transformers in Vision: Applications and Architectures

Covers the impact of transformers in computer vision, discussing their architecture, applications, and advancements in various tasks.