computer vision projects (:,5)

Computer Vision Group

Computer Vision Projects (:,5)

Vincenzo Caglioti

Giacomo Boracchi, Simone Gasparini, Alessandro Giusti, Pierluigi Taddei


Computer Vision Group Team

Vincenzo Caglioti Giacomo Boracchi, Simone Gasparini, Alessandro Giusti, Pierluigi Taddei


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).


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).


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…


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.


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’’


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


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


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



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



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


Motion Estimation from a Single Blurred Image

Image Restoration: De-Blurring• Build a “Blur Map”• Adapt Existing De-blurring Techniques to real blurred images


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


Robbery detection

Face and hands detectionFace and hands detection


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


Rectification of perspective images

Objective: removing perspective effect from images

Perspective Image Rectified Image


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


Rectification of perspective images

Available project:• 3D reconstruction of urban scene from uncalibrated images for

virtual tourCoordinator: Caglioti


Calibration of catadioptric camera

Catadioptric camera: a perspective camera placed in front of a curved mirror

Catadioptric camera Catadioptric images

MirrorMirror

CameraCamera


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


License Plate Recognition

Objective: automatically detect and recognize license plate from video sequences on a dsp-equipped camera.

YZH 4025


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


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


Thank you…

Further informations avaialble at www.elet.polimi.it/people/caglioti/

{caglioti | boracchi | gasparini | giusti | taddei}@elet.polimi.it

computer vision projects (:,5)

Documents