P. Mazzeo | Università Del Salento (original) (raw)

Papers by P. Mazzeo

Proceedings of the 2008 international conference on Content-based image and video retrieval - CIVR '08, 2008

In the last decade, several research efforts have been undertaken in soccer video analysis. This ... more In the last decade, several research efforts have been undertaken in soccer video analysis. This increasing interest is motivated by the possible applications over a wide spectrum of topics: indexing, summarization, video enhancement, team and players statistics, tactic analysis, referee's support, etc. Soccer video analysis requires different challenging tasks: ball and players have to be localized in each frame, tracked over time and, above all, their interactions have to be detected and analyzed. The latter task is fundamental, especially for statistics and referee decision support purposes, but, unfortunately, it has not received adequate attention from the scientific community. In this paper a multi-view system able to understand in real time the interactions between the ball and the players is presented. 3D ball trajectories are extracted by triangulation from multiple cameras and used to detect the interactions between the players and the ball. Inference processes are then introduced to determine the player kicking the ball and to fix the instant of the interaction. The system has been tested during several matches of the Italian first division soccer championship and experimental proofs of its effectiveness are reported.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010

In order to perform automatic analysis of sport videos acquired from a multi-sensing environment,... more In order to perform automatic analysis of sport videos acquired from a multi-sensing environment, it is fundamental to face the problem of automatic football team discrimination. A correct assignment of each player to the relative team is a preliminary task that together with player detection and tracking algorithms can strongly affect any high level semantic analysis. Supervised approaches for object

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009

People Tracking is a problem of great interest for wide areas video surveillance systems. In thes... more People Tracking is a problem of great interest for wide areas video surveillance systems. In these large areas, it is not possible for a single camera to observe the complete area of interest. Surveillance systems architecture requires algorithms with the ability to track objects while observing them through multiple cameras. We focus our work on multi camera tracking with non overlapping fields of view (FOV). In particular we propose a multi camera architecture for wide area surveillance and a real time people tracking algorithm across non overlapping cameras. In this scenario it is necessary to track object both in intracamera and inter-camera FOV. We consider these problems in this paper. In particular we have investigated different techniques to evaluate intra-camera and inter-camera tracking based on color histogram. For the intra-camera tracking we have proposed different methodologies to extract the color histogram information from each object patches. For inter-camera tracking we have compared different methods to evaluate the colour Brightness Transfer Function (BTF) between non overlapping cameras. These approaches are based on color histogram mapping between pairs of images of the same object in different FOVs. Therefore we have combined different methodology to calculate the color histogram in order to estimate different colour BTF performances. Preliminary results demonstrates that the proposed method combined with BTF outperform the performance in terms of matching rate between different cameras.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009

ABSTRACT Visual surveillance is often based on background subtraction; it usually detects moving ... more ABSTRACT Visual surveillance is often based on background subtraction; it usually detects moving regions in a rough way, with the presence of shadows, ghosts and reflections. In order to improve quality of segmented objects by removing these artifacts in this work we propose an approach based on edge matching. The basic idea is that edges extracted in shadow (or ghost) regions in current image exactly match with edges extracted in the same regions in the background image. On the contrary, edges extracted on foreground objects have not correspondent edges in the background image. A preliminary segmentation procedure based on the uniformity of photometric gain between adjacent points has been carried out to allow a better shadow removing. The algorithm has been tested in many different real contexts, both in indoor and outdoor context.

6th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2009, 2009

The problem of ground truth generation is fundamental for many approaches of computer vision and ... more The problem of ground truth generation is fundamental for many approaches of computer vision and image processing. In order to test algorithms for object segmentation, object tracking, object interactions, it is necessary to have image sequences in which the ground truth is determined in an objective way. In the context of visual surveillance where many people moves in the scene occluding each other, it could be very complex and hard the work of generating for each image the position of all the moving objects and maintain this information for all the period in which they remain in the scene. In this paper we propose a semi-automatic system that generates an initial ground truth estimation, and then provides a user-friendly interface to manually validate or correct the track results. The proposed system has been tested on some soccer video sequences that have been published on-line for being available to the scientific community, but it can be used also in other surveillance contexts.

Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010, 2010

of them concerning the human silhouette analysis, and some others related to the ball and player ... more of them concerning the human silhouette analysis, and some others related to the ball and player kinematics. Experiments were carried out on a multi view image sequences of a public soccer data set.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010

ABSTRACT Automatic sport team discrimination, that is the correct assignment of each player to th... more ABSTRACT Automatic sport team discrimination, that is the correct assignment of each player to the relative team, is a fundamental step in high level sport video sequences analysis applications. In this work we propose a novel set of features based on a variation of classic color histograms called Positional Histograms: these features try to overcome the main drawbacks of classic histograms, first of all the weakness of any kind of relation between spectral and spatial contents of the image. The basic idea is to extract histograms as a function of the position of points in the image, with the goal of maintaining a relationship between the color distribution and the position: this is necessary because often the actors in a play field dress in a similar way, with just a different distribution of the same colors across the silhouettes. Further, different unsupervised classifiers and different feature sets are jointly evaluated with the goal of investigate toward the feasibility of unsupervised techniques in sport video analysis.

Computers in Railways X, 2006

ABSTRACT The correct assessment of the condition of a railroad requires the consideration of diff... more ABSTRACT The correct assessment of the condition of a railroad requires the consideration of different factors. Some factors, such as the condition of the ties, can be measured by inspecting features visible from the surface of the railway. Other factors include the condition of the ballast; it is important to recognize the critical situation in which any foreign object can be present on the ballast. These kinds of objects could be cans, pieces of sheet and everything over a well determined dimension. Extensive human resources are currently applied to the problem of evaluating railroad health. The proposed visual inspection system uses images acquired from a digital line scan camera installed under a train. Here we focus on the problem of foreign object detection in the railway maintenance context. To obtain this aim we train a Multilayer Perceptron Network (MLPN) with the edge histogram of the ballast patches manually extracted from the acquired digital image sequence. The general performances of the system, in terms of speed and detection rate, are mainly influenced by the adopted features for representing images and by their number. By this inspection system it is possible to aid the personnel in railway safety issues because a high detection rate percentage has been obtained. We show the adopted techniques by using images acquired in real experimental conditions. Keywords: obstacle detection, ballast inspection, neural networks. 1 Introduction Inspection of the rail state is one of the basic tasks in railway maintenance. In the last few years a large number of methods have been proposed by the computer vision community for facing the problem of visual inspection [1, 2]. The

Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05), 2005

Rail inspection is a very important task in railway maintenance and it is periodically needed for... more Rail inspection is a very important task in railway maintenance and it is periodically needed for preventing dangerous situations. Inspection is operated manually by trained human operator walking along the track searching for visual anomalies. This monitoring is unacceptable for slowness and lack of objectivity, because the results are related to the ability of the observer to recognize critical situations.

In the last decades the development of very high speed trains in railway transportation requires ... more In the last decades the development of very high speed trains in railway transportation requires new maintenance strategies. New trolleys equipped with innovative measuring systems have been employed for monitoring overhead lines (catenaries). Using this system gives two great advantages: i) the diagnose can be performed with a low level of breaking in railway traffic; ii) the monitoring can be executed at the same speed of ordinary locomotives in order to point out the stress suffered by mechanical components of the train and the railroad structure. In this paper we present a vision system for monitoring of the catenary staggering. We propose a new method which is able to measure the position of the overhead line by a stereovision system. All these sensors are installed on a innovative maintenance trolley. Experimental results in real context are presented.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010

In order to perform automatic analysis of sport videos acquired from a multi-sensing environment,... more In order to perform automatic analysis of sport videos acquired from a multi-sensing environment, it is fundamental to face the problem of automatic football team discrimination. A correct assignment of each player to the relative team is a preliminary task that together with player detection and tracking algorithms can strongly affect any high level semantic analysis. Supervised approaches for object

Rail inspection is a very important task in railway maintenance for traffic safety issues and in ... more Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required. Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the rail track searching for rail anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. The aim of this paper is to present a vision based technique to detect automatically the presence or absence of the fastening elements that fix the rail to the sleepers. The images are acquired by a digital line scan camera installed under a train. Subsequently these images are pre-processed by using wavelet transform with Haar and Daubechies approximation coefficients. The obtained coefficients are fed as input to two different neural networks: the first one identifies the bolts candidates and the second one validates the bolt recognition process. The final detecting system has been applied to a long sequence of real images showing a high reliability robustness and good performances.

2008 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008, 2008

ABSTRACT In the last decade, several research efforts have been undertaken in soccer video analys... more ABSTRACT In the last decade, several research efforts have been undertaken in soccer video analysis. This increasing interest is motivated by the possible applications over a wide spectrum of topics: indexing, summarization, video enhancement, team and players statistics, tactic analysis, refereepsilas support, etc. Soccer video analysis requires different challenging tasks: ball and players have to be localized in each frame, tracked over time and, above all, their interactions (passes/shoots) have to be detected and analyzed. The latter task is fundamental, especially for statistics and referee decision support purposes, but, unfortunately, it has not received adequate attention from the scientific community. In this paper a multi-view system able to understand in real time the interactions between the ball and the players is presented. The 3D ball trajectories are, firstly, extracted by triangulation from multiple fixed cameras and then projected on a virtual play-field where they are temporally analyzed to detect their variations generated by the interaction with the players. Inference processes are then introduced to fix the instant of the detected interaction and, finally, the player kicking the ball is identified by analyzing human body configuration with an innovative neural approach based on a Contourlet representation of human silhouette data. The system has been tested during several matches of the Italian first division football championship and experimental proofs of its effectiveness are reported.

Lecture Notes in Computer Science, 2014

Object tracking across multiple cameras is a very challenge issue in vision based monitoring appl... more Object tracking across multiple cameras is a very challenge issue in vision based monitoring applications. The selection of features is the first step to realize a reliable tracking algorithm. In this work we analyse TLD and Struck, which are two of the most cited real-time visual trackers proposed in the literature in last years. They use two different feature extraction methodologies, Fern and Haar, respectively. The idea of this work is to compare performance of these well known visual tracking algorithms replacing their original feature characterization methods with local feature-based visual representations. We test the improvement in terms of object detection and tracking performance grafting different features characterization into two completely different online tracker frameworks. The used feature extraction methods are based on Local Binary Pattern (LBP), Local Gradient Pattern (LGP) and Histogram of Oriented Gradients (HOG).

Lecture Notes in Computer Science, 2014

Paladyn, Journal of Behavioral Robotics, 2015

In this work, a real-time system able to automatically recognize soft-biometric traits is introdu... more In this work, a real-time system able to automatically recognize soft-biometric traits is introduced and used to improve the capability of a humanoid robot to interact with humans. In particular the proposed system is able to estimate gender and age of humans in images acquired from the embedded camera of the robot. This knowledge allows the robot to properly react with customized behaviors related to the gender/age of the interacting individuals. The system is able to handle multiple persons in the same acquired image, recognizing the age and gender of each person in the robot's field of view. These features make the robot particularly suitable to be used in socially assistive applications.

Pattern Analysis and Applications, 2015

Ball recognition in soccer matches is a critical issue for automatic soccer video analysis. Unfor... more Ball recognition in soccer matches is a critical issue for automatic soccer video analysis. Unfortunately, because of the difficulty in solving the problem, many efforts of numerous researchers have still not produced fully satisfactory results in terms of accuracy. This paper proposes a ball recognition approach that introduces a double level of innovation. Firstly, a randomized circle detection approach based on the local curvature information of the isophotes is used to identify the edge pixels belonging to the ball boundaries. Then, ball candidates are validated by a learning framework formulated into a threelayered model based on a variation of the conventional local binary pattern approach. Experimental results were obtained on a significant set of real soccer images, acquired under challenging lighting conditions during Italian ''Serie A'' matches. The results have been also favorably compared with the leading state-of-the-art methods.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009

ABSTRACT Motion detection algorithms usually detect moving regions in a rough way; in some applic... more ABSTRACT Motion detection algorithms usually detect moving regions in a rough way; in some application contexts it could be mandatory to obtain the exact shape of such objects by removing cast shadows as well as ghosts and reflections due to variations in light conditions. To address this problem we propose an approach based on edge matching. The basic idea is that edges extracted in shadow (or ghost) regions in current image exactly match with edges extracted in the correspondent regions in the background image. On the contrary, edges extracted on foreground objects have not correspondent edges in the background image. In order to remove all shadow regions instead of only shadow points, we firstly segment the foreground image into subregions, according to uniformity of photometric gain between adjacent points. The algorithm has been tested in many different real contexts, both in indoor and outdoor environments.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009

ABSTRACT Human action recognition is an important research area in the field of computer vision h... more ABSTRACT Human action recognition is an important research area in the field of computer vision having a great number of real-world applications. This paper presents a multi-view action recognition framework able to extract human silhouette clues from different synchronized static cameras and then to validate them by analyzing scene dynamics. Two different algorithmic procedures were introduced: the first one performs, in each acquired image, the neural recognition of the human body configuration by using a novel mathematical tool called Contourlet transform. The second procedure performs, instead, 3D ball and player motion analysis. The outcomes of both procedures are then merged to accomplish the final player action recognition task. Experiments were carried out on several image sequences acquired during some matches of the Italian "Serie A" soccer championship.

Proceedings of the 2008 international conference on Content-based image and video retrieval - CIVR '08, 2008

In the last decade, several research efforts have been undertaken in soccer video analysis. This ... more In the last decade, several research efforts have been undertaken in soccer video analysis. This increasing interest is motivated by the possible applications over a wide spectrum of topics: indexing, summarization, video enhancement, team and players statistics, tactic analysis, referee's support, etc. Soccer video analysis requires different challenging tasks: ball and players have to be localized in each frame, tracked over time and, above all, their interactions have to be detected and analyzed. The latter task is fundamental, especially for statistics and referee decision support purposes, but, unfortunately, it has not received adequate attention from the scientific community. In this paper a multi-view system able to understand in real time the interactions between the ball and the players is presented. 3D ball trajectories are extracted by triangulation from multiple cameras and used to detect the interactions between the players and the ball. Inference processes are then introduced to determine the player kicking the ball and to fix the instant of the interaction. The system has been tested during several matches of the Italian first division soccer championship and experimental proofs of its effectiveness are reported.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010

In order to perform automatic analysis of sport videos acquired from a multi-sensing environment,... more In order to perform automatic analysis of sport videos acquired from a multi-sensing environment, it is fundamental to face the problem of automatic football team discrimination. A correct assignment of each player to the relative team is a preliminary task that together with player detection and tracking algorithms can strongly affect any high level semantic analysis. Supervised approaches for object

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009

People Tracking is a problem of great interest for wide areas video surveillance systems. In thes... more People Tracking is a problem of great interest for wide areas video surveillance systems. In these large areas, it is not possible for a single camera to observe the complete area of interest. Surveillance systems architecture requires algorithms with the ability to track objects while observing them through multiple cameras. We focus our work on multi camera tracking with non overlapping fields of view (FOV). In particular we propose a multi camera architecture for wide area surveillance and a real time people tracking algorithm across non overlapping cameras. In this scenario it is necessary to track object both in intracamera and inter-camera FOV. We consider these problems in this paper. In particular we have investigated different techniques to evaluate intra-camera and inter-camera tracking based on color histogram. For the intra-camera tracking we have proposed different methodologies to extract the color histogram information from each object patches. For inter-camera tracking we have compared different methods to evaluate the colour Brightness Transfer Function (BTF) between non overlapping cameras. These approaches are based on color histogram mapping between pairs of images of the same object in different FOVs. Therefore we have combined different methodology to calculate the color histogram in order to estimate different colour BTF performances. Preliminary results demonstrates that the proposed method combined with BTF outperform the performance in terms of matching rate between different cameras.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009

ABSTRACT Visual surveillance is often based on background subtraction; it usually detects moving ... more ABSTRACT Visual surveillance is often based on background subtraction; it usually detects moving regions in a rough way, with the presence of shadows, ghosts and reflections. In order to improve quality of segmented objects by removing these artifacts in this work we propose an approach based on edge matching. The basic idea is that edges extracted in shadow (or ghost) regions in current image exactly match with edges extracted in the same regions in the background image. On the contrary, edges extracted on foreground objects have not correspondent edges in the background image. A preliminary segmentation procedure based on the uniformity of photometric gain between adjacent points has been carried out to allow a better shadow removing. The algorithm has been tested in many different real contexts, both in indoor and outdoor context.

6th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2009, 2009

The problem of ground truth generation is fundamental for many approaches of computer vision and ... more The problem of ground truth generation is fundamental for many approaches of computer vision and image processing. In order to test algorithms for object segmentation, object tracking, object interactions, it is necessary to have image sequences in which the ground truth is determined in an objective way. In the context of visual surveillance where many people moves in the scene occluding each other, it could be very complex and hard the work of generating for each image the position of all the moving objects and maintain this information for all the period in which they remain in the scene. In this paper we propose a semi-automatic system that generates an initial ground truth estimation, and then provides a user-friendly interface to manually validate or correct the track results. The proposed system has been tested on some soccer video sequences that have been published on-line for being available to the scientific community, but it can be used also in other surveillance contexts.

Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010, 2010

of them concerning the human silhouette analysis, and some others related to the ball and player ... more of them concerning the human silhouette analysis, and some others related to the ball and player kinematics. Experiments were carried out on a multi view image sequences of a public soccer data set.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010

ABSTRACT Automatic sport team discrimination, that is the correct assignment of each player to th... more ABSTRACT Automatic sport team discrimination, that is the correct assignment of each player to the relative team, is a fundamental step in high level sport video sequences analysis applications. In this work we propose a novel set of features based on a variation of classic color histograms called Positional Histograms: these features try to overcome the main drawbacks of classic histograms, first of all the weakness of any kind of relation between spectral and spatial contents of the image. The basic idea is to extract histograms as a function of the position of points in the image, with the goal of maintaining a relationship between the color distribution and the position: this is necessary because often the actors in a play field dress in a similar way, with just a different distribution of the same colors across the silhouettes. Further, different unsupervised classifiers and different feature sets are jointly evaluated with the goal of investigate toward the feasibility of unsupervised techniques in sport video analysis.

Computers in Railways X, 2006

ABSTRACT The correct assessment of the condition of a railroad requires the consideration of diff... more ABSTRACT The correct assessment of the condition of a railroad requires the consideration of different factors. Some factors, such as the condition of the ties, can be measured by inspecting features visible from the surface of the railway. Other factors include the condition of the ballast; it is important to recognize the critical situation in which any foreign object can be present on the ballast. These kinds of objects could be cans, pieces of sheet and everything over a well determined dimension. Extensive human resources are currently applied to the problem of evaluating railroad health. The proposed visual inspection system uses images acquired from a digital line scan camera installed under a train. Here we focus on the problem of foreign object detection in the railway maintenance context. To obtain this aim we train a Multilayer Perceptron Network (MLPN) with the edge histogram of the ballast patches manually extracted from the acquired digital image sequence. The general performances of the system, in terms of speed and detection rate, are mainly influenced by the adopted features for representing images and by their number. By this inspection system it is possible to aid the personnel in railway safety issues because a high detection rate percentage has been obtained. We show the adopted techniques by using images acquired in real experimental conditions. Keywords: obstacle detection, ballast inspection, neural networks. 1 Introduction Inspection of the rail state is one of the basic tasks in railway maintenance. In the last few years a large number of methods have been proposed by the computer vision community for facing the problem of visual inspection [1, 2]. The

Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05), 2005

Rail inspection is a very important task in railway maintenance and it is periodically needed for... more Rail inspection is a very important task in railway maintenance and it is periodically needed for preventing dangerous situations. Inspection is operated manually by trained human operator walking along the track searching for visual anomalies. This monitoring is unacceptable for slowness and lack of objectivity, because the results are related to the ability of the observer to recognize critical situations.

In the last decades the development of very high speed trains in railway transportation requires ... more In the last decades the development of very high speed trains in railway transportation requires new maintenance strategies. New trolleys equipped with innovative measuring systems have been employed for monitoring overhead lines (catenaries). Using this system gives two great advantages: i) the diagnose can be performed with a low level of breaking in railway traffic; ii) the monitoring can be executed at the same speed of ordinary locomotives in order to point out the stress suffered by mechanical components of the train and the railroad structure. In this paper we present a vision system for monitoring of the catenary staggering. We propose a new method which is able to measure the position of the overhead line by a stereovision system. All these sensors are installed on a innovative maintenance trolley. Experimental results in real context are presented.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2010

In order to perform automatic analysis of sport videos acquired from a multi-sensing environment,... more In order to perform automatic analysis of sport videos acquired from a multi-sensing environment, it is fundamental to face the problem of automatic football team discrimination. A correct assignment of each player to the relative team is a preliminary task that together with player detection and tracking algorithms can strongly affect any high level semantic analysis. Supervised approaches for object

Rail inspection is a very important task in railway maintenance for traffic safety issues and in ... more Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required. Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the rail track searching for rail anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. The aim of this paper is to present a vision based technique to detect automatically the presence or absence of the fastening elements that fix the rail to the sleepers. The images are acquired by a digital line scan camera installed under a train. Subsequently these images are pre-processed by using wavelet transform with Haar and Daubechies approximation coefficients. The obtained coefficients are fed as input to two different neural networks: the first one identifies the bolts candidates and the second one validates the bolt recognition process. The final detecting system has been applied to a long sequence of real images showing a high reliability robustness and good performances.

2008 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008, 2008

ABSTRACT In the last decade, several research efforts have been undertaken in soccer video analys... more ABSTRACT In the last decade, several research efforts have been undertaken in soccer video analysis. This increasing interest is motivated by the possible applications over a wide spectrum of topics: indexing, summarization, video enhancement, team and players statistics, tactic analysis, refereepsilas support, etc. Soccer video analysis requires different challenging tasks: ball and players have to be localized in each frame, tracked over time and, above all, their interactions (passes/shoots) have to be detected and analyzed. The latter task is fundamental, especially for statistics and referee decision support purposes, but, unfortunately, it has not received adequate attention from the scientific community. In this paper a multi-view system able to understand in real time the interactions between the ball and the players is presented. The 3D ball trajectories are, firstly, extracted by triangulation from multiple fixed cameras and then projected on a virtual play-field where they are temporally analyzed to detect their variations generated by the interaction with the players. Inference processes are then introduced to fix the instant of the detected interaction and, finally, the player kicking the ball is identified by analyzing human body configuration with an innovative neural approach based on a Contourlet representation of human silhouette data. The system has been tested during several matches of the Italian first division football championship and experimental proofs of its effectiveness are reported.

Lecture Notes in Computer Science, 2014

Object tracking across multiple cameras is a very challenge issue in vision based monitoring appl... more Object tracking across multiple cameras is a very challenge issue in vision based monitoring applications. The selection of features is the first step to realize a reliable tracking algorithm. In this work we analyse TLD and Struck, which are two of the most cited real-time visual trackers proposed in the literature in last years. They use two different feature extraction methodologies, Fern and Haar, respectively. The idea of this work is to compare performance of these well known visual tracking algorithms replacing their original feature characterization methods with local feature-based visual representations. We test the improvement in terms of object detection and tracking performance grafting different features characterization into two completely different online tracker frameworks. The used feature extraction methods are based on Local Binary Pattern (LBP), Local Gradient Pattern (LGP) and Histogram of Oriented Gradients (HOG).

Lecture Notes in Computer Science, 2014

Paladyn, Journal of Behavioral Robotics, 2015

In this work, a real-time system able to automatically recognize soft-biometric traits is introdu... more In this work, a real-time system able to automatically recognize soft-biometric traits is introduced and used to improve the capability of a humanoid robot to interact with humans. In particular the proposed system is able to estimate gender and age of humans in images acquired from the embedded camera of the robot. This knowledge allows the robot to properly react with customized behaviors related to the gender/age of the interacting individuals. The system is able to handle multiple persons in the same acquired image, recognizing the age and gender of each person in the robot's field of view. These features make the robot particularly suitable to be used in socially assistive applications.

Pattern Analysis and Applications, 2015

Ball recognition in soccer matches is a critical issue for automatic soccer video analysis. Unfor... more Ball recognition in soccer matches is a critical issue for automatic soccer video analysis. Unfortunately, because of the difficulty in solving the problem, many efforts of numerous researchers have still not produced fully satisfactory results in terms of accuracy. This paper proposes a ball recognition approach that introduces a double level of innovation. Firstly, a randomized circle detection approach based on the local curvature information of the isophotes is used to identify the edge pixels belonging to the ball boundaries. Then, ball candidates are validated by a learning framework formulated into a threelayered model based on a variation of the conventional local binary pattern approach. Experimental results were obtained on a significant set of real soccer images, acquired under challenging lighting conditions during Italian ''Serie A'' matches. The results have been also favorably compared with the leading state-of-the-art methods.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009

ABSTRACT Motion detection algorithms usually detect moving regions in a rough way; in some applic... more ABSTRACT Motion detection algorithms usually detect moving regions in a rough way; in some application contexts it could be mandatory to obtain the exact shape of such objects by removing cast shadows as well as ghosts and reflections due to variations in light conditions. To address this problem we propose an approach based on edge matching. The basic idea is that edges extracted in shadow (or ghost) regions in current image exactly match with edges extracted in the correspondent regions in the background image. On the contrary, edges extracted on foreground objects have not correspondent edges in the background image. In order to remove all shadow regions instead of only shadow points, we firstly segment the foreground image into subregions, according to uniformity of photometric gain between adjacent points. The algorithm has been tested in many different real contexts, both in indoor and outdoor environments.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009

ABSTRACT Human action recognition is an important research area in the field of computer vision h... more ABSTRACT Human action recognition is an important research area in the field of computer vision having a great number of real-world applications. This paper presents a multi-view action recognition framework able to extract human silhouette clues from different synchronized static cameras and then to validate them by analyzing scene dynamics. Two different algorithmic procedures were introduced: the first one performs, in each acquired image, the neural recognition of the human body configuration by using a novel mathematical tool called Contourlet transform. The second procedure performs, instead, 3D ball and player motion analysis. The outcomes of both procedures are then merged to accomplish the final player action recognition task. Experiments were carried out on several image sequences acquired during some matches of the Italian "Serie A" soccer championship.