Reliable-loc introduces a resilient LiDAR-based global localization system for wearable mapping devices in complex, GNSS-denied street environments with sparse features and incomplete prior maps. Key Highlights: Dual-Stage Observation Model for MCL: Fuses global and local features into Monte Carlo Localization (MCL), using spectral matching and pose error metrics to refine particle weights in feature-poor scenes.…
Ever heard of an AI cracking a coding bug that stumped a 30-year C++ FAANG veteran for four years and 200 hours of debugging? That just happened. The hero? Anthropic’s newly unveiled Claude 4. This isn’t just a cool story; it’s a preview of the serious firepower Anthropic is unleashing today with Claude Opus 4…
In the ever-evolving world of artificial intelligence, breakthroughs don’t always mean bigger models; they often mean smarter, more efficient architectures. Microsoft’s Phi-4 series is a perfect illustration of this principle. By harnessing advanced training techniques and high-quality curated data, Microsoft has engineered a family of small language models that excel at complex reasoning tasks, yet…
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…