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This is the world’s first SLAM dataset recorded onboard real roller coasters, offering extreme motion dynamics, perceptual challenges, and unique conditions for benchmarking SLAM algorithms under aggressive real-world trajectories. Key Highlights: Unprecedented Motion Dynamics – Captures high-acceleration motion with rapid velocity changes, sharp turns, and steep vertical drops, providing a stress test for visual-inertial odometry and…
The convenience of clicking “buy now” or instantly transferring funds has become second nature. But beneath this seamless digital surface lurks a rapidly growing shadow: online transaction fraud. This isn’t just a minor nuisance; it’s a global crisis. In 2024 alone, consumers reported staggering losses exceeding $12.5 billion due to fraud, a 25% jump from…
This paper introduces a SLAM framework that achieves real-time CPU-only performance in dense, registration-error-minimization-based odometry and mapping by leveraging exact point cloud downsampling via coreset extraction, eliminating the need for GPU acceleration. Key Highlights Exact Point Cloud Downsampling via Coresets – Selects a minimal subset of residuals that exactly preserve the quadratic registration error function for a given pose,…
In computer vision, detecting blobs(regions) that differ from their surroundings is a common and powerful technique. A blob can be as simple as a spot of light in an image or as complex as a moving object in a video. Blob detection is crucial in various domains such as microscopy, surveillance, object tracking, astronomy, and…
The OpenCV-SID Conference on Computer Vision and AI (OSCCA), OpenCV’s first ever in-person conference, is just a few days away! If you’re in the SF Bay Area, it is a can’t-miss event this May 12th. Let’s take a look at some of the speakers and topics you can expect to see on stage. Gary Bradski,…
Edge detection is a crucial technique in image processing and computer vision, used to identify sharp changes in brightness that typically signify object boundaries, edges, lines, or textures. It enables applications like object recognition, image segmentation, and tracking by highlighting the structural features of an image. In this blog, we’ll explore three of the most…
Image translation and rotation are two of the most common and essential operations in computer vision. Whether you’re aligning scanned documents, augmenting datasets for deep learning, correcting skewed camera input, or building a panorama stitching pipeline — these geometric transformations are at the core of modern image processing. In this tutorial, we’ll take a deep…
MP-SfM redefines classical Structure-from-Motion by tightly integrating monocular depth and surface normal priors into incremental SfM, enabling robust 3D reconstruction from sparse, unstructured image collections. Key Highlights: Monocular Depth + Surface Normal Fusion – Augments traditional SfM with priors from off-the-shelf deep networks (e.g., Metric3D-v2, DSINE), eliminating the need for three-view overlap. Two-View Track Reconstruction – Enables…
Image filtering is one of the fundamental building blocks of computer vision. Whether you’re smoothing an image to remove noise or enhancing features for better detection, filtering techniques based on convolution are everywhere. In this article, we’ll explore image filtering using convolution — understanding the mathematics behind it, and seeing how it’s practically implemented in…
Imagine this! A video of a world leader giving a speech they never actually delivered, or a celebrity appearing to endorse a product they’ve never even heard of. These aren’t simple photo edits—deepfakes are hyper-realistic, AI-generated videos, images, or audio clips that manipulate reality in ways previously reserved for science fiction. For example, a recent deepfake…