computer vision projects (:,5)
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Computer Vision Group
Computer Vision Projects (:,5)
Vincenzo Caglioti
Giacomo Boracchi, Simone Gasparini, Alessandro Giusti, Pierluigi Taddei
Computer Vision Group
Computer Vision Group Team
Vincenzo Caglioti Giacomo Boracchi, Simone Gasparini, Alessandro Giusti, Pierluigi Taddei
Computer Vision Group
Reconstructing Canal Surfaces, trajectories and spin of moving balls
We can reconstruct circular-cross section canal surfaces from a single image (main algorithms are already implemented in well-packaged Java methods).
Computer Vision Group
Project proposals
Explore possibilities for a 3D input device (maybe real-time?) with a webcam + flexible tube. Develop demo application (OpenGL or Java3D).
• Example: virtual flexible stick-figure.• Example: 3D modeling of flexible objects.• Be creative! :)• Requisites: learn principles of 3D visualization
Quantitatively evaluate performance of current algorithms, and test possible improvements. Implement camera autocalibration.
• Prerequisite: knowledge of camera calibration and projective geometry (Image Analysis and Synthesis classes).
Computer Vision Group
Other applications
With the same algorithm we can reconstruct the trajectory of a moving ball from a long-exposure photograph (no frame rate issues, can handle very fast games, any lighting condition, inexpensive equipment).
Reconstruct the trajectory of a real moving ball. Evaluate reconstruction accuracy. Can we also measure nonparabolic trajectories (e.g. Pirlo’s penalty kick, spinning table tennis shots, volleyball “floater” serves…)? Mostly implementation work, some interesting possible optimizations.
Implement an automatic refereeing system for table tennis. Implement a system for detecting the exact bounce position of a fast-moving ball from its blurred
trail (“in or out?”). Augment low-frame rate videos of table tennis matches (think of the new Shell’s TV advertisement).
For example:• Draw ball “shadow” on the table (3D reconstruction)• Draw ball velocity vector• Predict the remaining trajectory portion• Manipulate the ball trail opacity and/or color (image processing)• Estimate ball speed• Synthethize a 100 fps slow motion replay from a 20 fps video…
Computer Vision Group
Ball spin from a single image (ongoing research)
If the ball surface is textured: analyze the trail and find the ball spin (axis and rotational speed) – ongoing research• 3D geometry issues• Image processing issues
Find ball spin axis and speed from traces left by dots on the ball surface (long-exposure).
Find ball spin axis and speed from blur of the ball’s surface features (short-exposure) -- joint work with Giacomo Boracchi.
Find ball spin speed from orthographic images (long-exposure) look for periodic color patterns.
Computer Vision Group
Tram transit detection and notification
A webcam will be placed on the DEI building pointing at Via Edoardo Bassini.
The video stream will be analized in order to detect the transit of any ATM tram, identifying its number and registering the transit time
A web framework will be then implemented in order to predict the next tram transit
The system will be exploited by the department employees in order to leave the office at the last usefull moment
Next predicted transits:
heading to Duomo: 5’ 23’’
heading to Lambrate: 2’12’’
Computer Vision Group
Structure from Motion
The aim is to reconstruct the 3D structure of a scene and the camera motion using as input only the video sequence caputred
Computer Vision Group
Project 1: Surface fitting
Given the 3D points and the initial image frames identify reliable surface patches onto which the initial images can be mapped
Coordinators: Caglioti, Taddei
Computer Vision Group
Project 2: Feature Tracking for Structure from Motion
The features tracked may disappear due to occlusion or to wrong matches between images
A good tracking algorithm should compensate for these effects and extract as many features as possible
Coordinators: Caglioti, Taddei
Computer Vision Group
Project 3: Paper Like surfaces
The object recorded is assumed to be a paper-like surface that is represented by a particular family: developable surfaces
The project will be aimed to build a framework to generate sintetic datas to test the alghoritms
Coordinators: Caglioti, Taddei
Computer Vision Group
Motion Estimation from a Single Blurred Image
Application: 3D reconstruction from a single image• Local motion extraction from blurred details (Corners/Texture)• Exploit Global Camera Movement
Computer Vision Group
Motion Estimation from a Single Blurred Image
Image Restoration: De-Blurring• Build a “Blur Map”• Adapt Existing De-blurring Techniques to real blurred images
Computer Vision Group
Objective: automatically detect holdup situations (“Hands Up!”) from video-surveillance sequences on a dsp-equipped camera.
Robbery detection
Background subtraction Detection of “hands up” pose
Color-based skin segmentation
Computer Vision Group
Robbery detection
Face and hands detectionFace and hands detection
Computer Vision Group
Robbery detection - Available projects
Pose recognition • Develop an approach based on silhouette extraction and pose
recognition
Face detection• Improve performance and robustness of face detector, test on a
larger training set
Hands detection• Develop a new detection algorithm (similar to the face detection
one) and test performance (hit rate and computational speed)
Skin segmentation• Improve performance of the skin detector using a voting system
involving three color spaces RGB, YCbCR, HUV.
Coordinators: Caglioti, Boracchi, Gasparini, Giusti, Taddei
Computer Vision Group
Rectification of perspective images
Objective: removing perspective effect from images
Perspective Image Rectified Image
Computer Vision Group
Natural image recognition through compression level analysis
Natural image recognition• Recognition of natural image (e.g. leaves, flowers) by
compressing the contour image and matching the compression levels
Coordinator: Caglioti
Original image Edge image
Computer Vision Group
Rectification of perspective images
Available project:• 3D reconstruction of urban scene from uncalibrated images for
virtual tourCoordinator: Caglioti
Computer Vision Group
Calibration of catadioptric camera
Catadioptric camera: a perspective camera placed in front of a curved mirror
Catadioptric camera Catadioptric images
MirrorMirror
CameraCamera
Computer Vision Group
Calibration of catadioptric camera
Calibration procedure• Develop a new calibration procedure for catadioptric cameras
from single image exploiting the silhouette of the mirror and the alignment constraints deriving from the image of straight lines.
Coordinator: Caglioti, Gasparini, Taddei
Computer Vision Group
License Plate Recognition
Objective: automatically detect and recognize license plate from video sequences on a dsp-equipped camera.
YZH 4025
Computer Vision Group
License Plate Recognition – Available Projects
New Starting ProjectNew Starting Project Probably Strict DeadlinesProbably Strict Deadlines ONLY THE BRAVES!ONLY THE BRAVES!
License Plate Detection Module• Develop a module that detect the license plate in image according
to color and shape
License Plate Recognition Module• Given the license plate image, develop a module that recognize
characters (e.g. using a neural network) and provide the license number
Both projects require good C-programming skills
Coordinators: Caglioti, Gasparini, Taddei
Computer Vision Group
Robot mapping
Objective: built a map of the environment collecting laser scans while robot is moving
Scanning while moving algorithm• Implement and test on a real robot (Mo.Ro 2) the mapping
algorithm− Coordinators: Caglioti, Gasparini
Map built by collecting scans
Laser scanner
Computer Vision Group
Thank you…
Further informations avaialble at www.elet.polimi.it/people/caglioti/
{caglioti | boracchi | gasparini | giusti | taddei}@elet.polimi.it
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