Novel Approches in Image Processing (IP) and Human Centred Systems (HCSs)

Transcription

1 Novel Approhes in Image Proessing (IP) and Human Centred Systems (HCSs) Giuseppe Plaidi, Danilo Avola, Andrea Petraa, Matteo Spezialetti University of L Aquila, Department of Life, Health and Environmental Sienes Via Vetoio Coppito 2, 67100, L Aquila, Italy {danilo.avola, andrea.petraa, giuseppe.plaidi, matteo.spezialetti}@univaq.it Luigi Cinque, Stefano Levialdi Sapienza University of Rome, Department of Computer Siene Via Salaria 113, 00198, Rome, Italy {inque, levialdi}@di.uniroma1.it Astrat The Image Proessing (IP) and Human Centred Systems (HCSs) are attrative and urrent topis of the Computer Siene (CS) field. This paper provides methods and algorithms to support these topis in everyday appliation environments (e.g., entrainment) as well as in speialisti ontexts (e.g., rehailitation). In partiular, it is foused on the dissemination of our most reent results otained in the following researh areas: Signal Proessing: we show our advanes in Image Proessing (IP) with respet to the following matters: Adaptive Aquisition and reonstrution of iomedial images, 3D Reonstrution of dental models, and Analysis of rain images. Human Centred Systems: we show our advanes in Human-Computer Interation (HCI) with respet to the following matters: Sketh Reognition, Gesture Reognition, and Handwriting Identifiation. We also present advanes in Human Body Modelling (inluding hands) and Human Body Reognition (HB-R) and Traking (HB-T) (inluding hands). Keywords: Image Proessing, Human-Centred Systems, Human-Computer Interation, Reognition and Traking of the Human Body 1. Introdution The next three su-setions summarizes reent works in IP, HCI, and HB-R & HB-T, respetively. Basi details and referenes are also given.

2 Figure 1. (a) reports the mask otained as union of a set of adaptive masks, () a visual prospetive during the implant design, () segmentation and laelling of an MRI rain slie. Image Proessing (IP) As regards the aquisition of iomedial images (Fig. 1a) we demonstrated that, y using adaptive methods and L 0 -homotopi minimization, we an reonstrut an image with a numer of samples whih is very lose to the sparsity oeffiient of the image without knowing a-priori the sparsity of the image. We highlighted two important aspets: 1) the width and the numer of samples of the starting dataset that initiate the adaptive proess, 2) how well the termination riteria allowed the aquisition of the optimal numer of oeffiients. The methods were tested on MRI ardia images as well as other iomedial images [1][2][3]. Moreover, most aquisition strategies have een presented for MRI, in order to eliminate the distortion effets due to magneti field inhomogeneity [3] [18]. As regards the 3D reonstrution of iomedial images (Fig. 1) we have foused on developing a general purpose framework to support the 3D reonstrution, rendering and proessing of iomedial images. Reently, we equipped the framework with a plug-in mehanism to proess any kind of image. Moreover, we implemented the Implant plug-in, a strutured omponent to model ustomised dental implants on a 3D representation of the oral avity derived from diagnosti images [4][5]. As regards the analysis of iomedial images (Fig. 1) we foused on developing the Texture ased Computer Aided Diagnosis Framework (T-CAD Framework), a general purpose framework to support the texture analysis and the morphologial reonstrution of rain MRI data. In partiular, we have demonstrated that a set of ustomized first and seond order statistis ased operators an e used to provide a mathematial desription of the rain tissues. The method an e applied on eah tissue of the human ody [6][7].

3 Figure 2. (a) reports the typial sketh omponents: freehand drawings and handwritten text. Eah omponent is reognized as text or drawing, susequently they are reognized and vetorized, () reports the working of a sketh-ased interfae ale to reognize the movements of a led pen, () reports a typial off-line input provided to a trained system whih will reognize the related writer. Human-Computer Interation (HCI) As regards the sketh reognition (Fig. 2a) we have foused on developing Sketh SeParatiOn and REognition Framework (SkethSPORE Framework), a system designed oth to automatially distinguish graphial from textual elements within the same sketh and to reognize freehand drawing as well as handwriting. Our reognition approah supports oth on-line and off-line modes, moreover it has een implemented aording to the XML poliies to failitate its integration with various appliations [8][9]. As regards the gesture reognition (Fig. 2) we have foused on developing different gesture-ased interfaes. We have oneived various approahes to reognize tools, hands, and ody gestures. We adopted different devies (e.g., Kinet, LEAP Motion) and designed ad-ho algorithms aording to the speifi appliation ontext. Reently, we have foused on the reognition of the ody, hands and fingers (without markers) to implement a set of Natural User Interfaes (NUIs) to support entrainment, ion rowsing, data managing, and rehailitation environments [10][11]. As regards the handwriting identifiation (Fig. 2) we have foused on analysing the handwriting to study different personal harateristis of the human sujets, inluding identity, harater, and neurologial disailities. Reently, we have oneived an handwriting identifiation approah ased on the omputation of the stati and dynami features of the strokes [12][13].

4 Figure 3. (a) reports the skeleton reognition of two human odies, () reports a sreenshot of the Swing exerise whih has een designed y onsidering that the patient has to maintain the equilirium standing on a virtual long arms Swing, () reports four hand poses. Reognition & Traking of the Human Body (HB-R & HB-T) As regards the human ody modelling and the human ody estimation and traking (Fig. 3a and Fig. 3) we have foused on developing different approahes to reonstrut and trak the volumetri shape of the ody as well as its skeleton. Reently, we have designed a framework supporting visionased gesture reognition and virtual environments for fast prototyping of ustomized exerises for rehailitation purposes. The goal was to provide skilled users with a tool for fast implementation and modifiation of speifi rehailitation exerises. We have also implemented a set of pilot examples [14][15]. As regards the hand modelling and the hand estimation and traking (Fig. 3) we have foused on developing different approahes to reonstrut and trak the skeleton of the hands and its joints. Reently, we have developed a virtual glove system whih an e adopted in different appliation ontexts [16]. Patents Some of the desried approahes are sujets of patents [17][18][19][20]. Referenes [1] L. Cianarella, D. Avola, G. Plaidi (2014). Adaptive Sampling and Reonstrution for Sparse Magneti Resonane Imaging. In Comp. Modeling of Ojets Presented in Images, Leture Notes in Computat. Vis. and Biome., Springer Int. Pu., Vol. 15, pp [2] G. Plaidi, D. Avola, L. Cinque, G. Mahiarelli, A. Petraa, M. Spezialetti (2014). Non Linear Reostrution for Adaptively Sampled Cardia Magneti Resonane Imaging Data. In Computational Modelling of Ojets Represented in Images: Fundamentals, Methods, and Appliations, Leture Note in Computer Siene, Springer Verlag, pp (in press). [3] G. Plaidi (2012). MRI: essentials for innovative tehnologies. CRC Press, [4] D. Avola, A. Petraa, G. Plaidi (2012). 3D Modelling to Support Dental Surgery. In Comp. Modelling of Ojets Represented in Images, Taylor & Franis Group, pp. 1 6.

5 [5] D. Avola, A. Petraa, G. Plaidi (2013). Design of a Framework for Personalised 3D Modelling from Medial Images. In Computer Methods in Biomehanis and Biomedial Engineering: Imaging & Visualization, Taylor & Franis Group, pp [6] D. Avola, L. Cinque, G. Plaidi (2012). Medial Image Analysis Through a Texture ased Computer Aided Diagnosis Framework. In International Journal of Biometris and Bioinformatis, Vol. 6, No. 5, pp [7] D. Avola, L. Cinque, G. Plaidi (2013). Customized First and Seond Order Statistis Based Operators to Support Advaned Texture Analysis of MRI Images. In Computational and Mathematial Methods in Mediine. Hindawi Pu. Corp., Vol. 2013, ID , pp [8] D. Avola, P. Bottoni, A. Dafinei, A. Laella (2011). FBD: An Agent-Based Arhiteture to Support Sketh Reognition Interfaes. In Proeedings of the 17th International Conferene on Distriuted Multimedia Systems, Knowledge Systems Institute, pp [9] D. Avola, L. Cinque, G. Plaidi (2013). SkethSPORE: A Sketh Based Domain Separation and Reognition System for Interative Interfaes. In Proeedings of the 17th International Conferene on Image Analysis and Proessing, LNCS, Vol. 8157, pp [10] D. Avola, P. Bottoni, A. Dafinei, A. Laella (2011). Color-Based Reognition of Gesturetraed 2D Symols. In Proeedings of the 7th International Conferene on Distriuted Multimedia Systems, Knowledge Systems Institute, pp [11] D. Avola, L. Cinque, S. Levialdi, G. Plaidi (2013). Human Body Language Analysis: A Preliminary Study Based on Kinet Skeleton Traking. In Pro. of the 17th International Conferene on Image Analysis and Proessing, SBA Work., LNCS, Vol. 8158, pp [12] D. Avola, A. Del Buono, P. Del Nostro, R. Wang (2009). A Novel Online Textual/Graphial Domain Separation Approah for Sketh-Based Interfaes. In 2nd International Symposium on Intelligent Interative Multimedia Systems and Servies. Springer Verlag, pp [13] D. Avola, L. Cinque, S. Levialdi, A. Petraa, G. Plaidi, M. Spezialetti (2014). Innovative On-Line Handwriting Identifiation Algorithm Based on Stroke Features. In Computational Modelling of Ojets Represented in Images: Fundamentals, Methods, and Appliations, Leture Note in Computer Siene, Springer Verlag, pp (in press). [14] D. Avola, M. Spezialetti, G. Plaidi (2013). Design of an Effiient Framework for Fast Prototyping of Customized HumanComputer Interfaes and Virtual Environments for Rehailitation. In Computers Methods and Programs in Biom., Vol. 110, No. 3, pp [15] D. Avola, L. Cinque, S. Levialdi, A. Petraa, G. Plaidi, M. Spezialetti (2014). Time-of- Flight Camera Based Virtual Reality Interation for Balane Rehailitation Purposes. In Computational Modelling of Ojets Represented in Images: Fundamentals, Methods, and Appliations, Leture Note in Computer Siene, Springer Verlag, pp (in press). [16] G. Plaidi, D. Avola, D. Iaoviello, L. Cinque (2013). Overall design and implementation of the virtual glove. In Computers in Biology and Mediine, Vol. 43, No. 11, pp [17] A. Galante, G. Plaidi (2013). Metodo ed Apparato per il Monitoraggio dell Esposizione Individuale a Campi Magnetii Statii o Quasi Statii. Patent Numer RM2013A [18] G. Plaidi (2007). Metodi di Codifia e Deodifia dei Segnali e Riostruzione di Immagini nel Dominio delle Aelerazioni Spaziali per Imaging e Spettrosopia di Risonanza Magnetia e Relativo Apparato. Patent Numer AQ2007A [19] G. Plaidi, F. Manasseri, A. Manini, F. Politi, M. Proietti (2006). Sistema Integrato per la Tempestiva Loalizzazione, Verifia della Presenza in Vita e Conteggio di Persone Investite dai Crolli di Edifii Causati dal Terremoto. Patent Numer AQ2006A [20] G. Plaidi, D. Franhi, G. Gualtieri, P. Gallo, L. Marsili, C. Marinellli, R. Passariello, L. Rosa, A. Sotgiu (2006). Sistema Ausiliario per L Effettuazione di Proedure Medihe Diagnostihe o Interventistihe Endoorporee in Vivo on uso Ridotto di Sansioni. Patent numer AQ2006A