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Frontend and UI
ar-runtime
AR headset runtime
Vision Pro, ARKit
System
Techniques · 8
Primitives · 27
ar-runtime
Foveated rendering
graphics · medium: Lower shading rate in the periphery via variable rate shading or multi-resolution, driven by eye tracking
Late latching reprojection
graphics · medium: Sample the newest head pose right before scanout and reproject the frame (ATW, ASW, spacewarp)
Levenberg marquardt
numerics · medium: Damped Gauss-Newton nonlinear least squares for model calibration
Bundle adjustment
robotics · medium: Jointly refine camera poses and 3D points by sparse nonlinear least squares on reprojection error
Camera calibration
robotics · medium: Intrinsic/extrinsic calibration (Zhang's method, distortion models, bundle adjustment)
Tsdf volume fusion
robotics · medium: Fuse depth frames into truncated signed distance volumes and extract meshes
Visual inertial odometry
robotics · medium: Fuse camera features with IMU preintegration in a filter or sliding-window optimizer for 6-DoF pose
Kalman filter
robotics · low: Optimal recursive estimator for a linear system with Gaussian noise: fuses a motion model with noisy measurements into a state estimate plus its covariance.
›
Homogeneous transforms
geometry · low: 4x4 affine and projective matrices, homogeneous coordinates, view and projection, normal matrices
Quaternion rotations
geometry · low: Unit quaternions as 3D rotations: 4 floats, cheap composition, no gimbal lock, plus the conversions, interpolation choices and numerical care needed in practice.
›
Vsync frame pacing
graphics · low: Vsync, swapchain presentation modes, frame pacing, latency and variable refresh
Lens distortion correction
graphics · low: Pre-warp rendered frames for headset optics: barrel distortion mesh and chromatic aberration
Feature detection orb
robotics · low: FAST corners with oriented BRIEF descriptors and Hamming matching for tracking and relocalization
Real time linux scheduling
embedded · low: PREEMPT_RT, SCHED_FIFO/DEADLINE, CPU isolation and mlockall for low-jitter loops
Ransac
robotics · low: Random sample consensus for robust model fitting with outliers (homographies, planes, poses)
GPU command buffers
graphics · low: Record GPU work as a flat list of commands on the CPU, submit it in batches, and reuse its memory through a ring of frames in flight guarded by fences.
›
Image resampling filters
graphics · low: Resize an image by convolving with a kernel (box, triangle, cubic, Lanczos) whose width scales with the shrink factor, done as two separable 1-D passes with precomputed weights.
›
Image warping remap
graphics · low: Resampling with lookup maps: resize, lens undistortion, homographies, bilinear/bicubic
Finite differences
numerics · low: Replace derivatives with weighted differences of grid values; simple stencils plus a stability condition (CFL) turn PDEs like heat, advection and waves into array loops.
›
LU and Cholesky factorization
numerics · low: Factor A = PLU (any square matrix, partial pivoting) or A = LLᵀ (SPD) once in O(n³), then solve each right-hand side in O(n²).
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Sparse matrices (CSR)
numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.
›
Rigid-body transforms (SE(3) poses)
robotics · low: Represent, compose, invert, integrate and interpolate 3D poses as unit quaternion plus translation, with exp/log maps for small motions and uncertainty.
›
Robust statistics
statistics · low: Location and scale estimates (median, MAD, trimmed mean, Huber M-estimator) that stay correct when a minority of the data is garbage.
›
+ 1 more techniques
+ 11 more primitives
System
Techniques · 8
Primitives · 27
ar-runtime
Foveated rendering
graphics · medium: Lower shading rate in the periphery via variable rate shading or multi-resolution, driven by eye tracking
Late latching reprojection
graphics · medium: Sample the newest head pose right before scanout and reproject the frame (ATW, ASW, spacewarp)
Levenberg marquardt
numerics · medium: Damped Gauss-Newton nonlinear least squares for model calibration
Bundle adjustment
robotics · medium: Jointly refine camera poses and 3D points by sparse nonlinear least squares on reprojection error
Camera calibration
robotics · medium: Intrinsic/extrinsic calibration (Zhang's method, distortion models, bundle adjustment)
Tsdf volume fusion
robotics · medium: Fuse depth frames into truncated signed distance volumes and extract meshes
Visual inertial odometry
robotics · medium: Fuse camera features with IMU preintegration in a filter or sliding-window optimizer for 6-DoF pose
Marching cubes
graphics · medium: Extract triangle meshes from scalar fields (marching cubes, dual contouring)
Kalman filter
robotics · low: Optimal recursive estimator for a linear system with Gaussian noise: fuses a motion model with noisy measurements into a state estimate plus its covariance.
›
Homogeneous transforms
geometry · low: 4x4 affine and projective matrices, homogeneous coordinates, view and projection, normal matrices
Quaternion rotations
geometry · low: Unit quaternions as 3D rotations: 4 floats, cheap composition, no gimbal lock, plus the conversions, interpolation choices and numerical care needed in practice.
›
Vsync frame pacing
graphics · low: Vsync, swapchain presentation modes, frame pacing, latency and variable refresh
Lens distortion correction
graphics · low: Pre-warp rendered frames for headset optics: barrel distortion mesh and chromatic aberration
Feature detection orb
robotics · low: FAST corners with oriented BRIEF descriptors and Hamming matching for tracking and relocalization
Real time linux scheduling
embedded · low: PREEMPT_RT, SCHED_FIFO/DEADLINE, CPU isolation and mlockall for low-jitter loops
Ransac
robotics · low: Random sample consensus for robust model fitting with outliers (homographies, planes, poses)
GPU command buffers
graphics · low: Record GPU work as a flat list of commands on the CPU, submit it in batches, and reuse its memory through a ring of frames in flight guarded by fences.
›
Image resampling filters
graphics · low: Resize an image by convolving with a kernel (box, triangle, cubic, Lanczos) whose width scales with the shrink factor, done as two separable 1-D passes with precomputed weights.
›
Image warping remap
graphics · low: Resampling with lookup maps: resize, lens undistortion, homographies, bilinear/bicubic
Finite differences
numerics · low: Replace derivatives with weighted differences of grid values; simple stencils plus a stability condition (CFL) turn PDEs like heat, advection and waves into array loops.
›
LU and Cholesky factorization
numerics · low: Factor A = PLU (any square matrix, partial pivoting) or A = LLᵀ (SPD) once in O(n³), then solve each right-hand side in O(n²).
›
Sparse matrices (CSR)
numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.
›
Rigid-body transforms (SE(3) poses)
robotics · low: Represent, compose, invert, integrate and interpolate 3D poses as unit quaternion plus translation, with exp/log maps for small motions and uncertainty.
›
Robust statistics
statistics · low: Location and scale estimates (median, MAD, trimmed mean, Huber M-estimator) that stay correct when a minority of the data is garbage.
›
PCA and SVD
machine-learning · low: Find orthogonal directions of maximum variance by an SVD of the centred data; randomized SVD gets the top k components in a few passes.
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GPU compute shaders
ml-training · low: The vendor-neutral GPU launch model of Metal, Vulkan and WebGPU: a grid of workgroups, shared memory, barriers and subgroups, driven by recorded command buffers.
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Spatial hashing
physics · low: Uniform grid stored in a hash table: bucket objects by cell, test only neighbouring cells; O(n) neighbour search for many similar-sized objects such as particles.
›
Image pyramids
graphics · low: Gaussian/Laplacian pyramids and tiled multi-resolution images for zoom and blending
Extended Kalman filter
robotics · low: Kalman filter for nonlinear motion and measurement models: linearize f and h with Jacobians at the current estimate each step. The default estimator in robot navigation.
›
Fast hash functions
data-structures · low: Non-cryptographic hashes built from 64×64→128-bit multiplies and xor-shifts; pick by key size, trust level and whether the hash is persisted.
›
Convolution image filters
graphics · low: Separable 2D convolution kernels for blur, sharpen (unsharp mask) and edges with border handling
Gpu synchronization fences
graphics · low: Fences, timeline semaphores and sync files between GPU queues, CPU and processes
Explicit Euler
numerics · low: Step an ODE forward by its current slope, y += h·f(t, y); first-order, one evaluation per step, the baseline every other integrator is measured against.
›
Thomas tridiagonal solver
numerics · low: O(n) tridiagonal linear solve used in implicit finite-difference and spline schemes
Parallel prefix sum
search-sort · low: Work-efficient scan (Blelloch, decoupled look-back) on CPU SIMD and GPUs; stream compaction
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