Automatic Fire Detection in Video Sequences

Turgay Celik (Eastern Mediterranean University, Turkey)

In this paper, we propose a real-time fire-detector which combines foreground information with statistical color information to detect fires. The foreground information which is obtained using adaptive background information is verified by the statistical color information which is extracted using hand labeled fire pixels to determine whether the detected foreground object is a candidate for fire or not. The output of the both stages is analyzed in consecutive frames which is the verification process of fire that uses the fact that fire never stays stable in visual appearance. The frame processing rate of the detector is about 30 fps with image size of 176x144 which enables the proposed detector to be applied for real-time applications.

Adding geometrical terms to shadow detection process

László Havasi (Peter Pazmany Catholic University, Hungary)

The elimination of strong shadow in outdoor scenes contain-ing human activity is addressed in the paper. The main con-tribution of the introduced method is the integration of geo-metrical information into the shadow detection process. This novel approach takes into account the collinearity of shadow and light direction and completed with a simple colour based pre-filtering. The final classification step is carried out via a Bayesian iteration scheme which is general enough to handle further characteristics of the problem: weak shadow and reflection.

Human Model and Motion Based 3D Action Recognition in Multiple View Scenarios

Cristian Canton (Universitat Politecnica de Catalunya, Spain); Josep Casas (UPC - Technical University of Catalonia, Spain); Montse Pardas (Technical University of Catalonia, Spain)

This paper presents a novel view-independent approach to the recognition of human gestures of several people in low resolution sequences from multiple calibrated cameras. In contraposition with other multi-ocular gesture recognition systems based on generating a classification on a fusion of features coming from different views, our system performs a data fusion (3D representation of the scene) and then a feature extraction and classification. Motion descriptors introduced by Bobick et al. for 2D data are extended to 3D and a set of features based on 3D invariant statistical moments are computed. A simple ellipsoid body model is fit to incoming 3D data to capture in which body part the gesture occurs thus increasing the recognition ratio of the overall system and generating a more informative classification output. Finally, a Bayesian classifier is employed to perform recognition over a small set of actions. Results are provided showing the effectiveness of the proposed algorithm in a SmartRoom scenario.

Visual speech detection using mouth region intensities

Spyridon Siatras (Aristotle University of Thessaloniki, Greece); Nikos Nikolaidis (Aristotle University of Thessaloniki, Greece); Ioannis Pitas (ARISTOTLE UNIVERSITY OF THESSALONIKI, Greece)

In recent research efforts, the integration of visual cues into speech analysis systems has been proposed with favorable response. This paper introduces a novel approach for lip activity and visual speech detection. We argue that the large deviation and increased values of the number of pixels with low intensities that the mouth region of a speaking person demonstrates can be used as visual cues for detecting speech. We describe a statistical algorithm, based on detection theory, for the efficient characterization of speaking and silent intervals in video sequences. The proposed system has been tested into a number of video sequences with encouraging experimental results. Potential applications of the proposed system include speech intent detection, speaker determination and semantic video annotation.

Cooperative Background Modelling using Multiple Cameras Towards Human Detection in Smart-Rooms

Jose-Luis Landabaso (Technical University of Catalunya, Spain); Montse Pardas (Technical University of Catalonia, Spain)

Shape-from-Silhouette (SfS) is the common approach taken to reconstruct the Visual Hull which is later used in 3D-trackers and body fitting techniques. The Visual Hull is defined as the intersection of the visual cones formed by the back-projection of several 2D binary silhouettes into the 3D space. Silhouettes are usually extracted using a foreground classification process, which is performed independently in each camera view. In this paper we present a novel approach in which 2D-foreground classification is achieved in 3D accordance in a Bayesian framework. In our approach, instead of classifying images and reconstructing later, we simultaneously reconstruct and classify in the 3D space.

Active Video-Surveillance Based on Stereo and Infrared Imaging

Gabriele Pieri (CNR, Inst. of Information Science and Technologies, Italy); Ovidio Salvetti (ISTI-CNR, Italy)

Video-surveillance is a very actual and critical issue at the present time. Within this topic we address the problem of firstly identifying moving people in a scene through motion detection techniques, and subsequently categorising them in order to identify humans for tracking their movements. The use of stereo cameras, coupled with infrared vision, allows to apply this technique to images acquired through different and variable condition, and allows an a priori filtering based on the characteristics of such images to give evidence to objects emitting an higher radiance (i.e. higher temperature).

Contour Based Smoke Detection in Video Using Wavelets

Behcet Toreyin (Bilkent University, Turkey); Yigithan Dedeoglu (Bilkent University, Turkey); A. Enis Cetin (Bilkent University, Turkey)

This paper proposes a novel method to detect smoke in video. It is assumed the camera monitoring the scene is stationary. The smoke is semi-transparent at the early stages of a fire. Therefore edges present in image frames start loosing their sharpness and this leads to a decrease in the high frequency content of the image. The background of the scene is estimated and decrease of high frequency energy of the scene is monitored using the spatial wavelet transforms of the current and the background images. Edges of the scene produce local extrema in the wavelet domain and a decrease in the energy content of these edges is an important indicator of smoke in the viewing range of the camera. Moreover, scene becomes grayish when there is smoke and this leads to a decrease in chrominance values of pixels. Periodic behavior in smoke boundaries is also analyzed using a Hidden Markov model (HMM) mimicking the temporal behavior of the smoke. In addition, boundary of smoke regions are represented in wavelet domain and high frequency nature of the boundaries of smoke regions is also used as a clue to model the smoke flicker.

Human Face Detection in Video Using Edge Projections

Mehmet Turkan (Bilkent University, Turkey); Ibrahim Onaran (Bilkent University, Turkey); Enis Çetin (Bilkent University, Turkey)

In this paper, a human face detection method in images and video is presented. After determining possible face candidate regions using color information, each region is filtered by a high-pass filter of a wavelet transform. In this way, edges of the region are highlighted, and a caricature-like representation of candidate regions is obtained. Horizontal, vertical and filter-like projections of the region are used as feature signals in dynamic programming (DP) and support vector machine (SVM) based classifiers. It turns out that SVM based classifier provides better detection rates compared to DP in our simulation studies.

Multimodal Fusion by Adaptive Compensation for Feature Uncertainty with Application to Audiovisual Speech Recognition

Athanassios Katsamanis (National Technical University of Athens, Greece); George Papandreou (National Technical University Athens, Greece); Vassilis Pitsikalis (National Technical University of Athens, Greece); Petros Maragos (National Technical University of Athens, Greece)

In pattern recognition one usually relies on measuring a set of informative features to perform tasks such as regression or classification. While the accuracy of feature measurements heavily depends on changing environmental conditions, studying the consequences of this fact has received relatively little attention to date. In this work we explicitly take into account uncertainty in feature measurements and we show in a rigorous probabilistic framework how the models used for classification should be adjusted to compensate for this effect. Our approach proves to be particularly fruitful in multimodal fusion scenarios, such as audio-visual speech recognition, where multiple streams of complementary features are integrated. For such applications, provided that an estimate of the measurement noise uncertainty for each feature stream is available, we show that the proposed framework leads to highly adaptive multimodal fusion rules which are widely applicable and easy to implement. We further show that previous multimodal fusion methods relying on stream weights fall under our scheme under certain assumptions; this provides novel insights into their applicability for various tasks and suggests new practical ways for estimating the stream weights adaptively. Preliminary experimental results in audio-visual speech recognition demonstrate the potential of our approach.

Opportunities and issues of Image Processing for Cultural Heritage Applications

Alessandro Piva (University of Florence, Italy); Vito Cappellini (University of Florence, Italy)

The application of image processing techniques for the analysis, the diagnostic and the restoration of artworks remains a very uncommon practise. Recently, however, there has been a greater interest on acquiring and processing image data of artworks: the efforts in this application field have been characterized by promising results, which proved the advantages that the use of digital image processing may have on several issues. In this paper the peculiarities and the state of the ar of this application field will be described.

Using Spanning Trees for Reduced Complexity Image Mosaicing

Nikos Nikolaidis (Aristotle University of Thessaloniki, Greece); Ioannis Pitas (ARISTOTLE UNIVERSITY OF THESSALONIKI, Greece)

Image mosaicing, i.e., reconstruction of an image from a set of overlapping sub-images, has numerous applications that include high resolution image acquisition of works of art. Unfortunately, optimal mosaicing has very large computational complexity that soon becomes prohibitive as the number of sub-images increases. In this paper, two methods which achieve significant computational savings by applying mosaicing in pairs of two sub-images at a time, without significant reconstruction losses, are proposed. Simulations are used to verify the computational efficiency and good performance in terms of matching error of the proposed techniques.

Automated Investigation of Archeological Vessels

Martin Kampel (Vienna University of Technology, Austria); Hubert Mara (Vienna University of Technology, Austria); Robert Sablatnig (Vienna University of Technology, Austria)

Motivated by the requirements of the present archaeology, we are developing an automated system for archaeological classification and reconstruction of ceramics. This paper shows a method to answer archaeological questions about the manufacturing process of ancient ceramics, which is important to determine the technological advancement of ancient culture. The method is based on the estimation of the pro- file lines of ceramic fragments, which can also be applied to complete vessels. With the enhancements shown in this paper, archaeologists get a tool to determine ancient manufacturing techniques.

Damages of Digitized Historical Images as Objects for Content Based Applications

Edoardo Ardizzone (Università degli Studi di Palermo, Italy); Haris Dindo (Università degli Studi di Palermo, Italy); Umberto Maniscalco (Istituto per le Applicazioni del Calcolo (I.A.C.) M. Picone - Italian National Research Council (C.N, Italy); Giuseppe Mazzola (Università degli Studi di Palermo, Italy)

This work presents the preliminary results achieved within a FIRB project aimed to develop innovative support tools for automatic or semi-automatic restoration of damaged digital images concerning archaeological and monumental inheritance of Mediterranean coast. In particular, this paper is focused on a methodology for describing image degradation and its meta-representation for content based storing and retrieval. Our innovative idea is to decompose and store in a conventional RDBMS the images content, considering the damages as objects of the images. Moreover, a set of descriptors(a subset of MPEG7 descriptors) is used for the damage meta representation aimed to content based application. Finally we developed a user-friendly database management tool for manipulating the contents of the database

The image processing system for art specimens: Nephele

Miroslav Benes (Institute of Information Theory and Automation, Czech Republic); Barbara Zitova (Institute of Information Theory and Automation, Czech Republic); Jan Flusser (Institute of Information Theory and Automation, Czech Republic); Janka Hradilova (Academic Laboratory of Materials Research of Paintings, Czech Republic); David Hradil (Academic Laboratory of Materials Research of Paintings, Czech Republic)

In our paper we introduce comprehensive solution for processing and archiving information about artwork specimens used in the course of art restoration - Nephele. The information processing based on image data is used in the procedure of identification of pigment and binder present in the artwork, which is very important issue for restorers. Proposed approach geometrically aligns images of microscopic cross-sections of artwork color layers - image registration method based on mutual information, and then creates preliminary color layer segmentation - modified k-means clustering. The archiving part of the Nephele enables creating database entries for painting materials research database, their storage, and creating text-based queries. In addition to these traditional database functions, advanced report retrieval is supported; based on the similarity of image data, comparing either the ultraviolet and visual spectra images (using co-occurence matrices and color similarity functions), or the energy dispersive X-ray images (using features computed from the wavelet decomposition of the data).

Multispectral UV Fluorescence Analysis of Painted Surfaces

Anna Pelagotti (INOA, Italy); Luca Pezzati (INOA, Italy); Alessandro Piva (University of Florence, Italy); Andrea Del Mastio (University of Florence - Media Integration and Communication Center, Italy)

A novel system has been developed to acquire digital multispectral ultraviolet (UV) induced visible fluorescence images of paintings. We present here the image processing needed to understand and further process the acquired multispectral UV fluorescence images.

Analysis of Multispectral Images of Paintings

Philippe Colantoni (Jean Monnet University, France); Ruven Pillay (C2RMF, France); Christian Lahanier (C2RMF, France); Denis Pitzalis (C2RMF, France)

One hundred paintings conserved in several museums have been scanned by the C2RMF using the multi-spectral CRISATEL camera. These high resolution images allow us to not only generate an accurate colour image under any chosen illuminant, but also allow us to reconstruct the reflectance spectra at each pixel. Such images can be used for a visual qualitative as well as measurement-based quantitative scientific analysis of the work of art. Several image processing tools have been developped to allow us to perform these analyses. The IIPImage system enables us to visualize high resolution multi-spectral 16 bit images, view image details in colour or for each spectral channel and to super-impose and compare different wavelengths. A complementary viewing system uses an innovative 3D graphics hardware-accelerated viewer to allow us to reconstruct the resulting colour dynamically while interactively changing the light spectrum. The system also allows us to perform segmentation, view the colour distribution for a particular colour-space and perform dynamic spectral reconstruction.

H.264 Coding Artifacts And Their Relation To Perceived Annoyance

Tobias Wolff (Darmstadt University of Technology, Germany); Hsin-Han Ho (University of California Santa Barbara, USA); John Foley (University of California Santa Barbara, USA); Sanjit K. Mitra (UCSB, USA)

In this study we investigate coding artifacts in H.264 baseline profile. A psychophysical experiment was conducted that collected data about the subjectively perceived annoyance of short video sequences as well as the perceived strength of three coding artifacts. The data provided by 52 subjects is analyzed with respect to bitrate and intra period of the encoded sequences. A new data analysis method is presented which is based on a granular data representation and enables the detection of multidimensional functional dependencies in data sets. This method is employed to establish a model for the perceived annoyance as a function of artifact strength.

Task impact on the visual attention in subjective image quality assessment

Alexandre Ninassi (University of Nantes, France); Olivier Le Meur (Thomson R&D, France); Patrick Le Callet (University of Nantes, France); Dominique Barba (Institut de Recherche en Communications et Cybernétique de Nantes, France); Arnaud Tirel (University of Nantes, France)

Visual attention is a main feature of the human visual system components. Knowing and using the mechanisms of the visual attention could help improving image quality assessment. But, which kind of saliency should be taken into account? A free-task visual selective attention or a quality oriented visual selective attention. We recorded and evaluated the discrepancy between these two types of visual attention. The results will be given to show the impact of the viewing task on visual strategy.

No-Reference perceptual quality assessment of colour image

Benjamin Bringier (SIC, Université de Poitiers, France); Noël RICHARD (Université de Poitiers, France); Chaker Larabi (SIC, Université de Poitiers, France); Christine Fernandez-Maloigne (SIC, Université de Poitriers, France)

Image quality assessment plays an important role in various image processing applications. In recent years, some objective image quality metrics correlated with perceived quality measurement have been developed. Two categories of metrics can be distinguished: with full-reference and noreference. Full-reference looks at decrease in image quality from some reference of ideal. No-reference approach attempts to model the judgment of image quality without the reference. Unfortunately, the universal image quality model is not on the horizon and empirical models establishes on psychophysical experimentation are generally used. In this paper, we present a new algorithm for quality assessment of colour reproduction based on human visual system modeling. A local contrast definition is used to assign quality scores. Finally, a good correlation is obtained between human evaluations and our method.

Estimation of accesible quality in noisy image compression

Nikolay Ponomarenko (National Aerospace University, Kharkov, Ukraine); Mikhail Zriakhov (National Aerospace University, Ukraine); Vladimir Lukin (National Aerospace University, Kharkov, Ukraine); Jaakko Astola (Tampere University of Technology, Finland); Karen Egiazarian (Tampere University of Technology, Finland)

A task of lossy compression of noisy images providing ac-cessible quality is considered. By accessible quality we mean minimal distortions of a compressed image with re-spect to the corresponding noise-free image that are ob-served for the case of optimal operation point (OOP). The ways of reaching OOP for noisy images are discussed. It is shown that this can be done in automatic mode with appro-priate accuracy. Investigations are performed for efficient DCT-based AGU coder for a set of test images. We also demonstrate that the proposed approach can be applied to automatic selection of compression ratio for lossy compres-sion of noise-free images.

No reference quality assessment of Internet multimedia services

Alessandro Neri (University of ROMA TRE, Italy); Marco Carli (University of Roma TRE, Italy); Marco Montenovo (HP C&I, Italy); Alessandro Perrot (HP C&I, Italy); Francesco Comi (University of Roma TRE, Italy)

In this paper an objective No Reference metric for assessing the quality degradations introduced by transmission over a heterogeneous IP network is presented. The proposed ap-proach is based on the analysis of the interframe correlation measured at the output of the rendering application. It does not require information about the kind of errors, delays and latencies that affected the link and countermeasures intro-duced by decoders in order to face the potential quality loss. Experimental results show the effectiveness of the proposed algorithm in approximating the assessments obtained with full reference metrics.

Intelligent Sharpness Enhancement for Video Post-Processing

Jorge Caviedes (Intel Corporation, USA)

Sharpness enhancement is one of the post-processing stages in the consumer electronics video chain that operates in an open-loop mode. Although adaptive behavior is possible, in general there is no feedback system aimed at maximizing perceived quality. In this paper we introduce a control system and metric for sharpness enhancement algorithms. We also discuss the options of implementing an internal or local control loop, i.e., to control the basic sharpness enhancement engine at the pixel or region level, and an external or global control loop for sharpness enhancement module.

4) Color Image Processing - 4 papers

Reduced-complexity Multiple Symbol Differential Detection for UWB Communications

Vincenzo Lottici (University of Pisa, Italy); Zhi Tian (Michigan Technological University, USA)

In ultra-wideband (UWB) communications, the typical signal propagation through dense multipath fading offers potentially very large multipath diversity, but at the same time complicates receiver design as far as channel estimation and multipath energy capture are concerned. To strike a desired balance, we propose a multi-symbol differential detection framework that bypasses training or costly channel estimation by the use of autocorrelation principle. Furthermore, resorting properly to the Viterbi algorithm enables to attain an efficient performance versus affordable complexity tradeoff solution. Simulation results demonstrate that the proposed detection scheme is remarkably robust with respect to the effects of both noise and multiple access interference.

UWB Receiver Design for low Resolution Quantization

Stefan Franz (University of Southern California, USA); Urbashi Mitra (University of Southern California, USA)

Digital implementation of ultra-wideband receivers requires analog-to-digital conversion (ADC) at an extremely high speed, thereby limiting the available bit resolution. Herein, a new family of receiver structures optimized and tailored to quantized observations is presented. The generalized-likelihood ratio test (GLRT) based on the quantized samples is derived and shown to provide performance improvements in comparison to the infinite resolution GLRT rule employed on the quantized received signal. Furthermore, simulation results reveal that four bits of resolution are sufficient to closely approach the performance of a full resolution receiver.

Narrowband Interference Suppression in Transmitted Reference UWB Receivers Using Sub-Band Notch Filters

Marco Pausini (Delft University of Technology, The Netherlands); Gerard Janssen (Delft University of Technology, The Netherlands)

The Transmitted-Reference (TR) signaling scheme in conjunction with the Auto-correlation Receivers (AcR) has gained popularity in the last few years as low-complexity system architecture for Ultra Wide Band (UWB) communications. Since the signal template is directly obtained from the received signal, not only the noise but also the interference caused by a narrowband (NB) system operating in the same bandwidth corrupt both the data and the reference pulses. In this paper we study the effects of a single-tone interferer on the performance of a TR systems, measured in terms of probability of error. We also propose a simple but effective way to counteract the NB interference, consisting of a bank of notch filters, suppressing the sub-band containing the NB signal.

Narrowband interference mitigation for a transmitted reference ultra-wideband receiver

Quang Hieu Dang (Delft University of Technology, The Netherlands); Alle Jan van der Veen (Delft University, The Netherlands)

Narrowband inteference (NBI) is of specific concern in transmitted reference ultrawide band (TR-UWB) communication systems. We consider NBI in high data rate applications where significant interframe interference is present due to a very short frame rate. Oversampling of the correlator output with respect to the frame rate is used to gather more information for the receiver. We formulate an approximate data model that includes the NBI terms, subsequently a receiver algorithm is derived.

Finger Selection for UWB Rake Receivers

Sinan Gezici (Princeton University, USA); Mung Chiang (Princeton University, USA); Hisashi Kobayashi (Princeton University, USA); H. Vincent Poor (Princeton University, USA)

The problem of choosing the multipath components to be employed at a selective Rake receiver, the finger selection problem, is considered for an impulse radio ultra-wideband system. First, the finger selection problem for MRC-Rake receivers is considered and the suboptimality of the conventional scheme is shown by formulating the optimal solution according to the SINR maximization criterion. Due to the complexity of the solution, a convex formulation is obtained by means of integer relaxation techniques. Then, the finger selection for MMSE-Rake receivers is studied and optimal and suboptimal schemes are presented. Finally, a genetic algorithm based solution is proposed for the finger selection problem, which works for various multipath combining schemes. Simulation studies are presented to compare the performance of different algorithms. Index Terms Ultra-wideband (UWB), impulse radio (IR), Rake receiver, convex optimization, integer programming, genetic algorithm (GA).

How to Efficiently Detect Different Data-Rate Communications in Multiuser Short-Range Impulse Radio UWB Systems

Simone Morosi (University of Firenze, Italy, Italy); Tiziano Bianchi (University of Florence, Italy)

Low and high data-rate applications can be foreseen for future ultra-wideband systems which are based on impulse radio and proper detection schemes have to be designed for the most general scenarios. In this paper an innovative frequency domain detection strategy is tested in two different indoor short-range communication scenarios where several mobile terminals transmit low or high data-rate flows to a base station. Both Zero Forcing (ZF) and Minimum Mean Square Error (MMSE) criteria have been investigated and compared with the classical RAKE. The results show that the proposed approach is well suited for the considered scenarios.

Reduced Memory Modeling and Equalization of Second order FIR Volterra Channels in Non-coherent UWB Systems

Jac Romme (IMST, Germany); Klaus Witrisal (Graz University of Technology, Austria)

This paper investigates a combination of two approaches to obtain high-data-rate UWB communication over multipath radio channels, using low complexity, non-coherent receivers. The first approach targets to equalize the occurring \emph{non-linear} ISI using trellis-based equalization, while the second approach aims to reduce or even avoid ISI by dividing the spectral resources into (a few) sub-bands. Combination of both concepts allows for a complexity trade-off between equalizer and RF front-end. Firstly, a reduced-memory data model will be introduced for the non-linear sub-band channels, optimal in the sense of the MMSE criterion. This model is used to study the relationship between equalizer complexity and performance. The second part of the paper investigates the performance of the complete system, before and after forward error control. The system uses QPSK-TR signaling, but the key concepts a