Pietro Azzari

People Tracking Using a Time-of-Flight Depth Sensor

Visually track several moving persons engaged in close interactions is known to be a very hard problem, though 3-D approaches based on stereo vision and plan-view maps offer much promise for dealing effectively with major issues such as occlusions and quick changes in body pose and appearance. However, in case of untextured scenes due to homogeneous objects or poor illumination, stereo-based tracking systems rapidly drop their performance. In this work, we present a real time people tracking system able to work even under severe low-lighting conditions. The system relies on a novel active sensor that provides brightness and depth images based on a Time of Flight (TOF) technology. The tracking algorithm is simple yet efficient, being based on geometrical constraints and invariants. Experiments accomplished under changing lighting conditions and involving multiple people closely interacting with each other have proved the reliability of the system.

An effective real-time mosaicing algorithm apt to detect motion through background subtraction using a PTZ camera

Nowadays, many visual surveillance systems exploit pan/tilt/zoom (PTZ) cameras to increase the field of view of a surveyed area. The background subtraction technique is widespread to detect moving objects with a high accuracy using one stationary camera. Extending such algorithms to work with moving cameras requires to have a background mosaic at ones disposal. Many solutions using mosaic background subtraction have been proposed, which offer real time capabilities or high quality of the detected objects. However, most of them rely on prior assumptions which limit the camera motion or the algorithm to work with a depth field of view only. In this work we propose some innovative solutions to achieve a real time mosaic background apt to work with existing background subtraction algorithms to yield excellent foreground object masks. Extensive experiments accomplished on challenging indoor and outdoor scenes permit to assess the quality of the mosaic as well as of the detected moving masks.

High-Quality Real Time Motion Detection Using PTZ Cameras

The approaches based on background difference are the most used with fixed cameras to perform motion detection, because of the high quality of the segmentation achieved. However, real time requirements prevent most of the algorithms proposed in literature to exploit the background difference with Pan-Tilt-Zoom (PTZ) cameras in real world applications. Nevertheless, using color information to detect motion yields a sensible improvement in terms of accuracy of segmented masks, by helping reducing camouflage and detecting shadows. To our knowledge, the algorithm we have conceived is the first to exploit color information and perform real time alignment and background difference based on background mosaicing, with PTZ cameras. In addition, no prior information regarding scene or camera parameters have been used for either spatial or tonal alignment. Accurate experiments performed on indoor and outdoor sequences allow to assess both quality and performance of the method we devised.

An Evaluation Methodology for Image Mosaicing Algorithms

Several image mosaicing algorithms claiming to advance the state of the art have been proposed so far. Though sometimes improvements can be recognised without quantitative evidences, the importance of a principled methodology to compare different algorithms is essential as this discipline evolves. Which is the best? What means the best? How to ascertain the supremacy? To answer such questions, in this paper we propose an evaluation methodology including standard data sets, ground-truth information and performance metrics. We also compare three variants of a well-known mosaicing algorithm according to the proposed methodology.

A Fast and reliable image mosaicing technique with application to wide area motion detection

Image mosaicing is stirring up a lot of interests in the research community for both its scientific significance and potential spinoff in real world applications. Being able to perform automatic image alignment in a common tonal and spatial reference can trigger a wide range of higher level image processing tasks such as panoramic image construction, scene depth computation, resolution enhancement, motion detection and tracking using non stationary camera. In this work we propose a fully automated real time on-line mosaicing algorithm able to build high quality seam-free panoramic images. Moreover, the whole approach does not exploit any a priori information regarding scene geometry, acquisition device properties or feedback signals, thus resulting in a fully image based solution. Extensive experiments have been accomplished to assess the quality of the attained mosaics by using them as the background to perform motion detection and tracking with a Pan Tilt Zoom camera.

A High Performance Exact Histogram Specification Algorithm

Real-time histogram specification methods aims to find a continuous function that transforms a source image to match a target distribution with the highest possible degree of accuracy. Many approaches privilege exact specification exploiting multi-valued ordering functions but incur in highly computational expensive implementations. Histogram specification algorithms can be classified according to computational complexity, image distortion and accuracy of reproduction of the target histogram. The method we propose permits an exact match of a given target histogram independently of the source image meanwhile introducing negligible image distortion. The simplicity of the method enables fast computation making the algorithm suitable for real time applications. Exhaustive experiments and accurate comparisons are carried out against the most representative approaches reported in literature.

Joint spatial and tonal mosaic alignment for motion detection with PTZ camera

Scene segmentation among background and foreground (moving) regions represents the first layer of many applications such as visual surveillance. Exploiting PTZ cameras permits to widen the field of view of a surveyed area and to achieve real object tracking through pan and tilt movements of the observer point of view. Having a mosaiced background allows a system to exploit the background subtraction technique even with moving cameras. Although spatial alignment issues have been thoroughly investigated, tonal registration has been often left out of consideration. This work presents a robust general purpose technique to perform spatial and tonal image registration to achieve a background mosaic without exploiting any prior information regarding the scene or the acquisition device. Accurate experiments accomplished on outdoor and indoor scenes assess the visual quality of the mosaic. Finally, the last experiment proves the effectiveness of using such a mosaic in our visual surveillance application.

Markerless Augmented Reality Using Image Mosaics

Augmented reality is a powerful tool for delivering spatially coherent information to a user moving in a known environment. Accurate and reliable pose estimation is the key to success. Many approaches track reference objects into the scene but as the environment grows larger more objects need to be tracked leading to computationally intensive methods. Instead, we propose a practical approach that is suitable for environment where big planar structures are present. All the objects laying on the structure are composed into a large reference object using image mosaicing techniques, so that the problem is reduced to that of finding the pose from a single plane. Experimental results show the effectiveness of this approach on two interesting case studies such as aeronautical servicing and cultural heritage.

Vision-Based Markerless Gaming Interface

The paper proposes a novel human machine interface for gaming applications based on computer vision. The key idea is to allow the user to interact with the game by simply moving a hand-held consumer grade camera. Detection of natural features in the incoming video stream avoids instrumenting the scene with optical markers while preserving real-time computation and accuracy. The paper presents also a prototype videogame developed as proof-of-concept of our camera-based gaming interface. Thanks to recent advances in real-time extraction and matching of natural features from images on mobile platforms, our proposal holds the potential to enable a new generation of camera-controlled videogames for hand-held mobile devices.