Company
vsys was founded 2016 to boost productization of computer vision technology in collaboration with international (and national) companies.
Domain
- image processing tasks
- real time and offline solutions
- Linux, Windows
- embedded systems, IoT
- pinhole and fisheye cameras
- RGB-D and stereo imaging
- multi-camera systems
- LIDAR
- camera calibration
- 3D reconstruction
- 2D/3D object detection/tracking
- custom neural networks
- Gaussian Splatting
- YOLO networks
- training data simulation (Blender)
- optical flow
- numerical optimization
- SLAM, graph optimization
- bundle adjustment
- image registration tasks
- point cloud processing
- panorama imaging
- OpenCV, OpenGL
- performance optimization
- GPU (CUDA, OpenCL, GLSL shaders)
- visualization
- background extraction
- motion capture systems
- custom algorithm development
- C++, Python, numpy, PyTorch
Selected projects
- Computer vision system for pool
- A real-time VR controller pose tracking algorithm
- Dense 3D reconstruction using moving monocular camera
- 2D ellipse detector for bin picking
- Upgrading stereo vision of a food delivery robot
- Real-time panorama stitching for food delivery robot
- VR controller detection from image using HoG
- HDR conversion for RGB-D based 3D mesh
- Low-cost computer vision system for tennis
- Stereo vision for autonomous driving
- Content pipeline from LIDAR to Unreal Engine
- Camera based car counter for parking lot monitoring
- Human 3D reconstruction using RGB-D sensor
- 2D trash tracking for analysing robot picking
- Plane sweep method for multi-view depth map generation
- Interactive and scalable 3D point cloud visualizer
Upgrading stereo vision of a food delivery robot
GPU implementation of semi-global block matcher for improving stereo depth map quality.
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Real-time panorama stitching for food delivery robot
Real-time panorama stitcher implemented using CUDA and OpenCL to Nvidia and Ryzen platforms.
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VR controller detection from image using HoG
Custom HoG detector trained using random forest and implemented in C++ to detect VR controller from 2D image.
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HDR conversion for RGB-D based 3D mesh
Upgrading 3D reconstructions into HDR space by modeling consumer camera exposure and gain mapping into unified color range.
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Low-cost computer vision system for tennis
Ball and player tracking for tennis with automatic calibration and spin detection. Platform: Yocto Linux.
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Stereo vision for autonomous driving
Stereo camera is setup on car rooftop for real-time depth perception. Depth image based object detection is also prototyped.
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Content pipeline from LIDAR to Unreal engine
Preprocessing pipeline to convert colored LIDAR point clouds into compressed and textured mesh format.
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Camera based car counter for parking lot monitoring
Real-time camera based car counter using optical flow on gates.
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Human 3D reconstruction using RGB-D sensor
Prototyping human 3D reconstruction using RGB-D sensor.
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2D trash tracking for analysing robot picking
Tracking trash feature points to solve the problem: What was picked?
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Plane sweep method for multi-view depth map generation
Generating a depth map using multiple calibrated views with high-reso images
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Interactive and scalable 3D point cloud visualizer
OpenGL based point cloud renderer using octree structure for traversing large point clouds
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Please send your inquiry below, if you need professional service, outsourcing or project execution in computer vision domain.