Fast 3D Rotation Estimation of Fruits Using Spheroid Models

[EN] Automated fruit inspection using cameras involves the analysis of a collection of views of the same fruit obtained by rotating a fruit while it is transported. Conventionally, each view is analyzed independently. However, in order to get a global score of the fruit quality, it is necessary to match the defects between adjacent views to prevent counting them more than once and assert that the whole surface has been examined. To accomplish this goal, this paper estimates the 3D rotation undergone by the fruit using a single camera. A 3D model of the fruit geometry is needed to estimate the rotation. This paper proposes to model the fruit shape as a 3D spheroid. The spheroid size and pose in each view is estimated from the silhouettes of all views. Once the geometric model has been fitted, a single 3D rotation for each view transition is estimated. Once all rotations have been estimated, it is possible to use them to propagate defects to neighbor views or to even build a topographic map of the whole fruit surface, thus opening the possibility to analyze a single image (the map) instead of a collection of individual views. A large effort was made to make this method as fast as possible. Execution times are under 0.5 ms to estimate each 3D rotation on a standard I7 CPU using a single core.Albiol Colomer, AJ.; Albiol Colomer, A.; Sánchez De Merás, C. (2021). Fast 3D Rotation Estimation of Fruits Using Spheroid Models. Sensors. 21(6):1-24. https://doi.org/10.3390/s21062232S12421

Precise eye localization using HOG descriptors

In this paper, we present a novel algorithm for precise eye detection. First, a couple of AdaBoost classifiers trained with Haar-like features are used to preselect possible eye locations. Then, a Support Vector Machine machine that uses Histograms of Oriented Gradients descriptors is used to obtain the best pair of eyes among all possible combinations of preselected eyes. Finally, we compare the eye detection results with three state-of-the-art works and a commercial software. The results show that our algorithm achieves the highest accuracy on the FERET and FRGCv1 databases, which is the most complete comparative presented so far. © Springer-Verlag 2010.This work has been partially supported by the grant TEC2009-09146 of the Spanish Government.Monzó Ferrer, D.; Albiol Colomer, A.; Sastre, J.; Albiol Colomer, AJ. (2011). Precise eye localization using HOG descriptors. 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Detection of Parked Vehicles using Spatio-temporal Maps

This paper presents a video-based approach to detect the presence of parked vehicles in street lanes. Potential applications include the detection of illegally and double-parked vehicles in urban scenarios and incident detection on roads. The technique extracts information from low-level feature points (Harris corners) to create spatiotemporal maps that describe what is happening in the scene. The method neither relies on background subtraction nor performs any form of object tracking. The system has been evaluated using private and public data sets and has proven to be robust against common difficulties found in closed-circuit television video, such as varying illumination, camera vibration, the presence of momentary occlusion by other vehicles, and high noise levels. © 2011 IEEE.This work was supported by the Spanish Government project Movilidad y automocion en Redes de Transporte Avanzadas (MARTA) under the Consorcios Estrategicos Nacionales de Investigacion Tecnologica (CENIT) program and the Comision Interministerial Ciencia Y Tecnologia (CICYT) under Contract TEC2009-09146. The Associate Editor for this paper was R. W. Goudy.Albiol Colomer, AJ.; Sanchis Pastor, L.; Albiol Colomer, A.; Mossi García, JM. (2011). Detection of Parked Vehicles using Spatio-temporal Maps. IEEE Transactions on Intelligent Transportation Systems. 12(4):1277-1291. https://doi.org/10.1109/TITS.2011.2156791S1277129112

Using latent features for short-term person re-identification with RGB-D cameras

This paper presents a system for people re-identification in uncontrolled scenarios using RGB-depth cameras. Compared to conventional RGB cameras, the use of depth information greatly simplifies the tasks of segmentation and tracking. In a previous work, we proposed a similar architecture where people were characterized using color-based descriptors that we named bodyprints. In this work, we propose the use of latent feature models to extract more relevant information from the bodyprint descriptors by reducing their dimensionality. Latent features can also cope with missing data in case of occlusions. Different probabilistic latent feature models, such as probabilistic principal component analysis and factor analysis, are compared in the paper. The main difference between the models is how the observation noise is handled in each case. Re-identification experiments have been conducted in a real store where people behaved naturally. The results show that the use of the latent features significantly improves the re-identification rates compared to state-of-the-art works.The work presented in this paper has been funded by the Spanish Ministry of Science and Technology under the CICYT contract TEVISMART, TEC2009-09146.Oliver Moll, J.; Albiol Colomer, A.; Albiol Colomer, AJ.; Mossi García, JM. (2016). Using latent features for short-term person re-identification with RGB-D cameras. Pattern Analysis and Applications. 19(2):549-561. https://doi.org/10.1007/s10044-015-0489-8S549561192http://kinectforwindows.org/http://www.gpiv.upv.es/videoresearch/personindexing.htmlAlbiol A, Albiol A, Oliver J, Mossi JM (2012) Who is who at different cameras. Matching people using depth cameras. Comput Vis IET 6(5):378–387Bak S, Corvee E, Bremond F, Thonnat M (2010) Person re-identification using haar-based and dcd-based signature. 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Lawrence Livermore National LaboratoryFreund Y, Iyer R, Schapire RE, Singer Y (2003) An efficient boosting algorithm for combining preferences. J Mach Learn Res 4:933–969Gandhi T, Trivedi M (2006) Panoramic appearance map (pam) for multi-camera based person re-identification. Advanced Video and Signal Based Surveillance, IEEE Conference on, p. 78Garcia J, Gardel A, Bravo I, Lazaro J (2014) Multiple view oriented matching algorithm for people reidentification. Ind Inform IEEE Trans 10(3):1841–1851Gheissari N, Sebastian TB, Hartley R (2006) Person reidentification using spatiotemporal appearance. CVPR 2:1528–1535Gray D, Brennan S, Tao H (2007) Evaluating appearance models for recognition, reacquisition, and tracking. In: Proceedings of IEEE international workshop on performance evaluation for tracking and surveillance (PETS)Gray D, Tao H (2008) Viewpoint invariant pedestrian recognition with an ensemble of localized features. 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Single Fusion Image from Collections of Fruit Views for Defect Detection and Classification

[EN] Quality assessment is one of the most common processes in the agri-food industry. Typically, this task involves the analysis of multiple views of the fruit. Generally speaking, analyzing these single views is a highly time-consuming operation. Moreover, there is usually significant overlap between consecutive views, so it might be necessary to provide a mechanism to cope with the redundancy and prevent multiple counting of defect points. This paper presents a method to create surface maps of fruit from collections of views obtained when the piece is rotating. This single image map combines the information contained in the views, thus reducing the number of analysis operations and avoiding possible miscounts in the number of defects. After assigning each piece a simple geometrical model, 3D rotation between consecutive views is estimated only from the captured images, without any further need for sensors or information about the conveyor. The fact that rotation is estimated directly from the views makes this novel methodology readily usable in high throughput industrial inspection machines without any special hardware modification. As proof of this technique's usefulness, an application is shown where maps have been used as input to a CNN to classify oranges into different categories.Albiol Colomer, AJ.; Sánchez De-Merás, CJ.; Albiol Colomer, A.; Hinojosa, S. (2022). Single Fusion Image from Collections of Fruit Views for Defect Detection and Classification. Sensors. 22(14):1-14. https://doi.org/10.3390/s22145452114221

Restricted Boltzmann Machines for Gender Classification

This paper deals with automatic feature learning using a generative model called Restricted Boltzmann Machine (RBM) for the problem of gender recognition in face images. The RBM is presented together with some practical learning tricks to improve the learning capabilities and speedup the training process. The performance of the features obtained is compared against several linear methods using the same dataset and the same evaluation protocol. The results show a classification accuracy improvement compared with classical linear projection methods. Moreover, in order to increase even more the classification accuracy, we have run some experiments where an SVM is fed with the non-linear mapping obtained by the RBM in a tandem configuration.Mansanet Sandin, J.; Albiol Colomer, A.; Paredes Palacios, R.; Villegas, M.; Albiol Colomer, AJ. (2014). Restricted Boltzmann Machines for Gender Classification. Lecture Notes in Computer Science. 8814:274-281. doi:10.1007/978-3-319-11758-4_30S2742818814Bengio, Y., Courville, A., Vincent, P.: Representation learning: A review and new perspectives. IEEE Trans. on PAMI 35(8), 1798–1828 (2013)Bressan, M., Vitrià, J.: Nonparametric discriminant analysis and nearest neighbor classification. Pattern Recognition Letters 24(15), 2743–2749 (2003)Buchala, S., et al.: Dimensionality reduction of face images for gender classification. In: Proceedings of the Intelligent Systems, vol. 1, pp. 88–93 (2004)Cai, D., He, X., Hu, Y., Han, J., Huang, T.: Learning a spatially smooth subspace for face recognition. In: CVPR, pp. 1–7 (2007)Courville, A., Bergstra, J., Bengio, Y.: Unsupervised models of images by spike-and-slab rbms. In: ICML, pp. 1145–1152 (2011)Huang, G.B., et al.: Labeled faces in the wild: A database for studying face recognition in unconstrained environments. Technical Report 07–49, Univ. of Massachusetts (October 2007)Schmah, T., et al.: Generative versus discriminative training of rbms for classification of fmri images. In: NIPS, pp. 1409–1416 (2008)Graf, A.B.A., Wichmann, F.A.: Gender classification of human faces. In: Bülthoff, H.H., Lee, S.-W., Poggio, T.A., Wallraven, C. (eds.) BMCV 2002. LNCS, vol. 2525, pp. 491–500. Springer, Heidelberg (2002)He, X., Niyogi, P.: Locality preserving projections. In: NIPS (2004)Hinton, G.E.: Training products of experts by minimizing contrastive divergence. Neural Comput. 14(8), 1771–1800 (2002)Hinton, G.E.: A practical guide to training restricted boltzmann machines. Technical report, University of Toronto (2010)Hinton, G.E., Salakhutdinov, R.: Reducing the dimensionality of data with neural networks. Science 313(5786), 504–507 (2006)Moghaddam, B., Yang, M.-H.: Learning gender with support faces. IEEE Trans. on PAMI 24(5), 707–711 (2002)Nair, V., Hinton, G.E.: 3d object recognition with deep belief nets. In: NIPS, pp. 1339–1347 (2009)Salakhutdinov, R., Mnih, A., Hinton, G.: Restricted boltzmann machines for collaborative filtering. In: ICML, pp. 791–798 (2007)Shan, C.: Learning local binary patterns for gender classification on real-world face images. Pattern Recognition Letters 33(4), 431–437 (2012)Shobeirinejad, A., Gao, Y.: Gender classification using interlaced derivative patterns. In: ICPR, pp. 1509–1512 (2010)Villegas, M., Paredes, R.: Dimensionality reduction by minimizing nearest-neighbor classification error. Pattern Recognition Letters 32(4), 633–639 (2011

Estimating Point of Regard with a Consumer Camera at a Distance

In this work, we have studied the viability of a novel technique to estimate the POR that only requires video feed from a consumer camera. The system can work under uncontrolled light conditions and does not require any complex hardware setup. To that end we propose a system that uses PCA feature extraction from the eyes region followed by non-linear regression. We evaluated three state of the art non-linear regression algorithms. In the study, we also compared the performance using a high quality webcam versus a Kinect sensor. We found, that despite the relatively low quality of the Kinect images it achieves similar performance compared to the high quality camera. These results show that the proposed approach could be extended to estimate POR in a completely non-intrusive way.Mansanet Sandin, J.; Albiol Colomer, A.; Paredes Palacios, R.; Mossi García, JM.; Albiol Colomer, AJ. (2013). Estimating Point of Regard with a Consumer Camera at a Distance. En Pattern Recognition and Image Analysis. Springer Verlag. 7887:881-888. doi:10.1007/978-3-642-38628-2_104S8818887887Baluja, S., Pomerleau, D.: Non-intrusive gaze tracking using artificial neural networks. Technical report (1994)Breiman, L.: Random forests. Machine Learning (2001)Logitech HD Webcam C525, http://www.logitech.com/es-es/webcam-communications/webcams/hd-webcam-c525Chang, C.-C., Lin, C.-J.: LIBSVM: A library for support vector machines. ACM TIST (2011), Software, http://www.csie.ntu.edu.tw/~cjlin/libsvmDrucker, H., Burges, C., Kaufman, L., Smola, A., Vapnik, V.: Support vector regression machines (1996)Hansen, D.W., Ji, Q. In: the eye of the beholder: A survey of models for eyes and gaze. IEEE Transactions on PAMI (2010)Ji, Q., Yang, X.: Real-time eye, gaze, and face pose tracking for monitoring driver vigilance. Real-Time Imaging (2002)Kalman, R.E.: A new approach to linear filtering and prediction problems. Transactions of the ASME–Journal of Basic Engineering (1960)Microsoft Kinect, http://www.microsoft.com/en-us/kinectforwindowsTimmerman, M.E.: Principal component analysis (2nd ed.). i. t. jolliffe. Journal of the American Statistical Association (2003)Morimoto, C.H., Mimica, M.R.M.: Eye gaze tracking techniques for interactive applications. Comput. Vis. Image Underst. (2005)Pirri, F., Pizzoli, M., Rudi, A.: A general method for the point of regard estimation in 3d space. In: Proceedings of the IEEE Conference on CVPR (2011)Reale, M.J., Canavan, S., Yin, L., Hu, K., Hung, T.: A multi-gesture interaction system using a 3-d iris disk model for gaze estimation and an active appearance model for 3-d hand pointing. IEEE Transactions on Multimedia (2011)Saragih, J.M., Lucey, S., Cohn, J.F.: Face alignment through subspace constrained mean-shifts. In: International Conference of Computer Vision, ICCV (2009)Kar-Han, T., Kriegman, D.J., Ahuja, N.: Appearance-based eye gaze estimation. In: Applications of Computer Vision (2002)Takemura, K., Kohashi, Y., Suenaga, T., Takamatsu, J., Ogasawara, T.: Estimating 3d point-of-regard and visualizing gaze trajectories under natural head movements. In: Symposium on Eye-Tracking Research and Applications (2010)Villanueva, A., Cabeza, R., Porta, S.: Eye tracking: Pupil orientation geometrical modeling. Image and Vision Computing (2006)Williams, O., Blake, A., Cipolla, R.: Sparse and semi-supervised visual mapping with the s3gp. In: IEEE Computer Society Conference on CVPR (2006

The role of virtual motor rehabilitation: a quantitative analysis between acute and chronic patients with acquired brain injury

"(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."Acquired brain injury (ABI) is one of the main problems of disability and death in the world. Its incidence and survival rate are increasing annually. Thus, the number of chronic ABI patients is gradually growing. Traditionally, rehabilitation programs are applied to postacute and acute patients, but recent publications determine that chronic patients may benefit from rehabilitation. Also, in the last few years, the potential of virtual rehabilitation (VR) systems has been demonstrated. However, until now, no previous studies have been carried out to compare the evolution of chronic patients with acute patients in a VR program. To perform this study, we developed a VR system for ABI patients. The system, vestibular virtual rehabilitation (V2R), was designed with clinical specialists. V2R has been tested with 21 people ranging in age from 18 to 80 years old that were classified in two groups: chronic patients and acute patients. The results demonstrate a similar recovery for chronic and acute patients during the intervention period. Also, the results showed that chronic patients stop their improvement when they finish their training. This conclusion encourages us to direct our developments toward VR systems that can be easily integrated at home, allowing chronic patients to have a permanent VR training program.This work was supported by the Ministerio de Educacion y Ciencia Spain: Projects Consolider-C (SEJ2006-14301/PSIC), "CIBER of Physiopathology of Obesity and Nutrition, an initiative of ISCIII," and the Excellence Research Program PROMETEO (Generalitat Valenciana. Conselleria de Educacion, 2008-157).Albiol Pérez, S.; Gil-Gómez, J.; Llorens Rodríguez, R.; Alcañiz Raya, ML.; Colomer Font, C. (2014). The role of virtual motor rehabilitation: a quantitative analysis between acute and chronic patients with acquired brain injury. IEEE Journal of Biomedical and Health Informatics. 18(1):391-398. https://doi.org/10.1109/JBHI.2013.2272101S39139818

Dispositivo y procedimiento de obtención de imágenes densitométricas de objetos mediante combinación de sistemas radiológicos y cámaras de profundidad

Dispositivo y procedimiento de obtención de imágenes densitométricas que comprende al menos un dispositivo radiológico, al menos un sensor de profundidad y medios de procesado de imágenes que combinan la información de absorción radiológica del conjunto de imágenes radiológicas registradas obtenido con los sistemas radiológicos con unas distancias de material atravesado que proporciona la reconstrucción tridimensional de los objetos obtenida de los sensores de profundidadPeer reviewedConsejo Superior de Investigaciones Científicas, Universidad Politécnica de Valencia, Universidad de ValenciaB1 Patente sin examen previ

Dispositivo y procedimiento de obtención de imágenes densitométricas de objetos mediante combinación de sistemas radiológicos y cámaras de profundidad

[EN] A device and a method for obtaining densitometric images comprise at least one X-ray device, at least one depth sensor, and image processing means which combine the X-ray absorptiometry information from the set of recorded X-ray images obtained with the X-ray systems with distances through the material, providing three-dimensional reconstruction of the objects by means of the depth sensors[ES] Dispositivo y procedimiento de obtención de imágenes densitométricas que comprende al menos un dispositivo radiológico, al menos un sensor de profundidad y medios de procesado de imágenes que combinan la información de absorción radiológica del conjunto de imágenes radiológicas registradas obtenido con los sistemas radiológicos con unas distancias de material atravesado que proporciona la reconstrucción tridimensional de los objetos obtenida de los sensores de profundidadPeer reviewedConsejo Superior de Investigaciones Científicas, Universidad Politécnica de Valencia, Universidad de ValenciaA1 Solicitud de patente con informe sobre el estado de la técnic