Changelog
COLMAP 3.6 (07/24/2020)
Improved robustness and faster incremental reconstruction process
Add
image_deleter
command to remove images from sparse modelAdd
image_filter
command to filter bad registrations from sparse modelAdd
point_filtering
command to filter sparse model point cloudsAdd
database_merger
command to merge two databases, which is useful to parallelize matching across different machinesAdd
image_undistorter_standalone
to enable undistorting images without a pre-existing full sparse modelImproved undistortion for fisheye cameras and FOV camera model
Support for masking input images in feature extraction stage
Improved HiDPI support in GUI for high-resolution monitors
Import sparse model when launching GUI from CLI
Faster CPU-based matching using approximate NN search
Support for bundle adjustment with fixed extrinsics
Support for fixing existing images when continuing reconstruction
Camera model colors in viewer can be customized
Support for latest GPU architectures in CUDA build
Support for writing sparse models in Python scripts
Scripts for building and running COLMAP in Docker
Many more bug fixes and improvements to code and documentation
COLMAP 3.5 (08/22/2018)
COLMAP is now released under the BSD license instead of the GPL
COLMAP is now installed as a library, whose headers can be included and libraries linked against from other C/C++ code
Add hierarchical mapper for parallelized reconstruction or large scenes
Add sparse and dense Delaunay meshing algorithms, which reconstruct a watertight surface using a graph cut on the Delaunay triangulation of the reconstructed sparse or dense point cloud
Improved robustness when merging different models
Improved pre-trained vocabulary trees available for download
Add COLMAP as a software entry under Linux desktop systems
Add support to compile COLMAP on ARM platforms
Add example Python script to read/write COLMAP database
Add region of interest (ROI) cropping in image undistortion
Several import bug fixes for spatial verification in image retrieval
Add more extensive continuous integration across more compilation scenarios
Many more bug fixes and improvements to code and documentation
COLMAP 3.4 (01/29/2018)
Unified command-line interface: The functionality of previous executables have been merged into the
src/exe/colmap.cc
executable. The GUI can now be started using the commandcolmap gui
and other commands are available ascolmap [command]
. For example, the feature extractor is now available ascolmap feature_extractor [args]
while all command-line arguments stay the same as before. This should result in much faster project compile times and smaller disk space usage of the program. More details about the new interface are documented at https://colmap.github.io/cli.htmlMore complete depth and normal maps with larger patch sizes
Faster dense stereo computation by skipping rows/columns in patch match, improved random sampling in patch match, and faster bilateral NCC
Better high DPI screen support for the graphical user interface
Improved model viewer under Windows, which now requires Qt 5.4
Save computed two-view geometries in database
Images (keypoint/matches visualization, depth and normal maps) can now be saved from the graphical user interface
Support for PMVS format without sparse bundler file
Faster covariant feature detection
Many more bug fixes and improvements
COLMAP 3.3 (11/21/2017)
Add DSP (Domain Size Pooling) SIFT implementation. DSP-SIFT outperforms standard SIFT in most cases, as shown in “Comparative Evaluation of Hand-Crafted and Learned Local Features”, Schoenberger et al., CVPR 2017
Improved parameters dense reconstruction of smaller models
Improved compile times due to various code optimizations
Add option to specify camera model in automatic reconstruction
Add new model orientation alignment based on upright image assumption
Improved numerical stability for generalized absolute pose solver
Support for image range specification in PMVS dense reconstruction format
Support for older Python versions in automatic build script
Fix OpenCV Fisheye camera model to exactly match OpenCV specifications
COLMAP 3.2 (9/2/2017)
Fully automatic cross-platform build script (Windows, Mac, Linux)
Add multi-GPU feature extraction if multiple CUDA devices are available
Configurable dimension and data type for vocabulary tree implementation
Add new sequential matching mode for image sequences with high frame-rate
Add generalized relative pose solver for multi-camera systems
Add sparse least absolute deviation solver
Add CPU/GPU options to automatic reconstruction tool
Add continuous integration system under Windows, Mac, Linux through Github
Many more bug fixes and improvements
COLMAP 3.1 (6/15/2017)
Add fast spatial verification to image retrieval module
Add binary file format for sparse models by default. Old text format still fully compatible and possible conversion in GUI and CLI
Add cross-platform little endian binary file reading and writing
Faster and less memory hungry stereo fusion by computing consistency on demand and possible limitation of image size in fusion
Simpler geometric stereo processing interface. Now geometric stereo output can be computed using a single pass
Faster and multi-architecture CUDA compilation
Add medium quality option in automatic reconstructor
Many more bug fixes and improvements
COLMAP 3.0 (5/22/2017)
Add automatic end-to-end reconstruction tool that automatically performs sparse and dense reconstruction on a given set of images
Add multi-GPU dense stereo if multiple CUDA devices are available
Add multi-GPU feature matching if multiple CUDA devices are available
Add Manhattan-world / gravity alignment using line detection
Add CUDA-based feature extraction useful for usage on clusters
Add CPU-based feature matching for machines without GPU
Add new THIN_PRISM_FISHEYE camera model with tangential/radial correction
Add binary to triangulate existing/empty sparse reconstruction
Add binary to print summary statistics about sparse reconstruction
Add transitive feature matching to transitively complete match graph
Improved scalability of dense reconstruction by using caching
More stable GPU-based feature matching with informative warnings
Faster vocabulary tree matching using dynamic scheduling in FLANN
Faster spatial feature matching using linear index instead of kd-tree
More stable camera undistortion using numerical Newton iteration
Improved option parsing with some backwards incompatible option renaming
Faster compile times by optimizing includes and CUDA flags
More stable view selection for small baseline scenario in dense reconstruction
Many more bug fixes and improvements
COLMAP 2.1 (12/7/2016)
Support to only index and match specific images in vocabulary tree matching
Support to perform image retrieval using vocabulary tree
Several bug fixes and improvements for multi-view stereo module
Improved Structure-from-Motion initialization strategy
Support to only reconstruct the scene using specific images in the database
Add support to merge two models using overlapping registered images
Add support to geo-register/align models using known camera locations
Support to only extract specific images in feature extraction module
Support for snapshot model export during reconstruction
Skip already undistorted images if they exist in output directory
Support to limit the number of features in image retrieval for improved speed
Miscellaneous bug fixes and improvements
COLMAP 2.0 (9/8/2016)
Implementation of dense reconstruction pipeline
Improved feature matching performance
New bundle adjuster for rigidly mounted multi-camera systems
New generalized absolute pose solver for multi-camera systems
New executable to extract colors from all images
Boost can now be linked in shared and static mode
Various bug fixes and performance improvements
COLMAP 1.1 (5/19/2016)
Implementation of state-of-the-art image retrieval system using Hamming embedding for vocabulary tree matching. This should lead to much improved matching results as compared to the previous implementation.
Guided matching as an optional functionality.
New demo datasets for download.
Automatically switch to PBA if supported by the project.
Implementation of EPNP solver for local pose optimization in RANSAC.
Add option to extract upright SIFT features.
Saving JPEGs in superb quality by default in export.
Add option to clear matches and inlier matches in the project.
New fisheye camera models, including the FOV camera model used by Google Project Tango (Thomas Schoeps).
Extended documentation based on user feedback.
Fixed typo in documentation (Thomas Schoeps).
COLMAP 1.0 (4/4/2016)
Initial release of COLMAP.