Publications

In this paper, we present a new approach to object tracking based on batteries of particle filter working in multicamera systems with non overlapped fields of view. In each view the moving objects are tracked with independent particle filters; each filter exploits a likelihood function based on both color and motion information. The consistent labeling of people exiting from a camera field of view and entering in a neighbor one is obtained sharing particles information for the initialization of new filtering trackers. The information exchange algorithm is based on path-nodes, which are a graph-based scene representation usually adopted in computer graphics. The approach has been tested even in case of simultaneous transitions, occlusions, and groups of people. Promising results have been obtained and here presented using a real setup of non overlapped cameras.

This paper reports an application of trajectory analysis in which forensics and video surveillance techniques are jointly employed for providing a new tool of multimedia forensics. Advanced video surveillance techniques are used to extract from a multi-camera system the trajectories of the moving people which are then modelled by either their positions (projected on the ground plane) or their directions of movement. Both these two representations can be very suitable for querying large video repositories, by searching for similar trajectories in terms of either sequences of positions or trajectory shape (encoded as sequence of angles, where positions do not care). Preliminary examples of the possible use of this approach are shown.

This article presents a framework for automatic semantic annotation of video streams with an ontology that includes concepts expressed using linguistic terms and visual data.

Ambient Intelligence (AmI) is an emerging field of research that comprises new paradigms, techniques and systems for intelligent processing of distributed sensing. A challenging arena for AmI framework is represented by urban environments that are characterized by high complexity, numerous sources of data,and spreading of interesting and non-trivial applications. In this context, the project LAICA (Laboratory of Ambient Intelligence for a friendly city) represents a real experiment of the usefulness of AmI for advanced services to citizens. This chapter will address solutions of video analysis that can be directly applied in urban AmI. It describes in details the uniqueness of LAICA approach, focusing in particular on the use of computer vision techniques for monitoring public parks. People surveillanceand web-based video broadcasting will be taken into account.

It is our great pleasure to welcome you to the 1st ACM Workshop on Multimedia in Forensics -- MiFor'09.With the proliferation of multimedia data on the web, surveillance cameras in cities, and mobile phones in everyday life we see an enormous growth in multimedia data that needs to be analyzed by forensic investigators. The sheer volume of such datasets makes manual inspection of all data impossible. Tools are needed to support the investigator in their quest for relevant clues and evidence and in their strive towards preventing crime.The multimedia community has developed new solutions for management of large collections of video footage, images, audio and other multimedia content, knowledge extraction and categorization, pattern recognition, indexing and retrieval, searching, browsing and visualization, and modeling and simulation in various domains. Due to the inherent uncertainty and complexity of forensic data, applying those techniques to forensic data is not straightforward. The time is ripe to tailor these results for forensics. Multimedia in forensics is the workshop which target is to join the research topics and the applications.The workshop aims at addressing the multimedia toolbox supporting the forensic process from the prevention of crime, capturing and annotation of the crime scene, the investigation of the data in the lab, up to the presentation of the results in court. It is a first attempt in bringing multimedia tools in to this exciting application field. The target audience consists of researchers working on innovative technology, representatives from companies developing tools, and forensic investigators in various disciplines.Despite the ambitious objective for the workshop and it being the first edition, it attracted a good number of quality submissions fairly distributed among different countries and among the different topics of the workshop. The MiFor09 Technical Program Committee includes the most experienced researchers in the related research fields, and thanks to their indispensable effort we were able to select 11 papers for oral presentation.The workshop schedules four oral sessions, named "Detection and Mining", "Multimedia forensics prototypes", "Forgery and Splicing Detection" and "Tracking". In addition, the program includes a keynote address by Professor Mohan Kankanhalli, a distinguished lecturer in the field.

This chapter will address most of the aspects of modern video surveillance with the reference to the research activity conducted at University of Modena and Reggio Emilia, Italy, within the scopes of the national FREE SURF (FREE SUrveillance in a pRivacy-respectFul way) and NATO-funded BE SAFE (Behavioral lEarning in Surveilled Areas with Feature Extraction) projects. Moving object detection and tracking from a single camera, multi-camera consistent labeling and trajectory shape analysis for path classification will be the main topics of this chapter.

In this paper we present an overview of the historical evolution of connected component labeling algorithms, and in particular the ones applied on images stored in raster scan order. This brief survey aims at providing a comprehensive comparison of their performance on modern architectures, since the high availability of memory and the presence of caches make some solutions more suitable and fast. Moreover we propose a new strategy for label propagation based on a 2x2 blocks, which allows to improve the performance of many existing algorithms. The tests are conducted on high resolution images obtained from digitized historical manuscripts and a set of transformations is applied in order to show the algorithms behavior at different image resolutions and with a varying number of labels.

In this paper a document analysis tool for historical manuscripts is proposed. The goal is to automatically segment layout components of the page, that is text, pictures and decorations. We specifically focused on the pictures, proposing a set of visual features able to identify significant pictures and separating them from all the floral and abstract decorations. The analysis is performed by blocks using a limited set of color and texture features, including a new texture descriptor particularly effective for this task, namely Gradient Spatial Dependency Matrix. The feature vectors are processed by an embedding procedure which allows increased performance in later SVM classification.

This paper proposes a real-time system capable to extract andmodel object trajectories from a multi-camera setup with theaim of identifying abnormal paths. The trajectories are modeledas a sequence of positional distributions (2D Gaussians)and clustered in the training phase by exploiting an innovativedistance measure based on a global alignment techniqueand Bhattacharyya distance between Gaussians. An on-lineclassification procedure is proposed in order to on-the-fly classifynew trajectories into either “normal” or “abnormal” (in thesense of rarely seen before, thus unusual and potentially interesting).Experiments on a real scenario will be presented.