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Tracking dynamic textures using a particle filter driven by intrinsic motion information

MACHINE VISION AND APPLICATIONS 2011年第5期22卷 781-789页

作者： Peteri, Renaud Univ La Rochelle Math Image & Applicat Lab MIA F-17042 La Rochelle France

In this paper, a new method for tracking dynamic textures is presented. Its novelty is to use a particle filter driven by the intrinsic motion of the tracked dynamic texture. Many research works have indeed shown that dynamic textures are well characterized by their intrinsic motion (in proceedings of 4th international conference on computer recognition systems CORES'05, pp. 17-26, 2005). In this work, we compute motion statistics of dynamic textures and use them in the observation model of our particle filter. Our tracking method is successfully applied on test sequences. The algorithm is fast and is able to track a dynamic texture moving on another dynamic texture with different intrinsic dynamics. The method is also able to track a dynamic texture in cases where classical particle filters based on color information only fail. Comments and future prospects raised by this method are finally described.

关键词： Dynamic textures Intrinsic motion Tracking Particle filtering condensation algorithm

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Comparison of stochastic filtering methods for 3D tracking

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PATTERN RECOGNITION 2011年第1-11期44卷 2711-2737页

作者： Salih, Yasir Malik, Aamir Saeed Univ Teknol PETRONAS Dept Elect & Elect Engn Perak Malaysia Univ Teknol Petronas Dept Elect & Elect Engn Tronoh Malaysia

In the recent years, the 3D visual research has gained momentum with publications appearing for all aspects of 3D including visual tracking. This paper presents a review of the literature published for 3D visual tracking over the past five years. The work particularly focuses on stochastic filtering techniques such as particle filter and Kalman filter. These two filters are extensively used for tracking due to their ability to consider uncertainties in the estimation. The improvement in computational power of computers and increasing interest in robust tracking algorithms lead to increase in the use of stochastic filters in visual tracking in general and 3D visual tracking in particular. Stochastic filters are used for numerous applications in the literature such as robot navigation, computer games and behavior analysis. Kalman filter is a linear estimator which approximates system's dynamics with Gaussian model while particle filter approximates system's dynamics using weighted samples. In this paper, we investigate the implementation of Kalman and particle filters in the published work and we provide comparison between these techniques qualitatively as well as quantitatively. The quantitative analysis is in terms of computational time and accuracy. The quantitative analysis has been implemented using four parameters of the tracked object which are object position, velocity, size of bounding ellipse and orientation angle. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Kalman filter 3D tracking Motion cue Particle filter condensation algorithm Articulated object tracking

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Appearance-based Human Gesture Recognition using Multimodal Features for Human Computer Interaction

Appearance-based Human Gesture Recognition using Multimodal ...

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Conference on Human Vision and Electronic Imaging XVI

作者： Luo, Dan Gao, Hua Ekenel, Hazim Kemal Ohya, Jun Waseda Univ Shinjuku Ku 1-3-10 Nishi Waseda Tokyo Japan Karlsrule Inst Tech Karlsruhe Germany

ISBN: (纸本)9780819484024

The use of gesture as a natural interface plays an utmost important role for achieving intelligent Human Computer Interaction (HCI). Human gestures include different components of visual actions such as motion of hands, facial expression, and torso, to convey meaning. So far, in the field of gesture recognition, most previous works have focused on the manual component of gestures. In this paper, we present an appearance-based multimodal gesture recognition framework, which combines the different groups of features such as facial expression features and hand motion features which are extracted from image frames captured by a single web camera. We refer 12 classes of human gestures with facial expression including neutral, negative and positive meanings from American Sign Languages (ASL). We combine the features in two levels by employing two fusion strategies. At the feature level, an early feature combination can be performed by concatenating and weighting different feature groups, and LDA is used to choose the most discriminative elements by projecting the feature on a discriminative expression space. The second strategy is applied on decision level. Weighted decisions from single modalities are fused in a later stage. A condensation-based algorithm is adopted for classification. We collected a data set with three to seven recording sessions and conducted experiments with the combination techniques. Experimental results showed that facial analysis improve hand gesture recognition, decision level fusion performs better than feature level fusion.

关键词： Gesture Recognition condensation algorithm Facial Expression

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3D Tracking of Laparoscopic Instruments Using Statistical and Geometric Modeling

3D Tracking of Laparoscopic Instruments Using Statistical an...

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14th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2011)

作者： Wolf, Remi Duchateau, Josselin Cinquin, Philippe Voros, Sandrine UJF Grenoble 1 CNRS F-38041 Grenoble France UJF Grenoble 1 CNRS INSERM TIMC IMAG UMR 5525 F-38041 Grenoble France

ISBN: (纸本)9783642236228

During a laparoscopic surgery, the endoscope can be manipulated by an assistant or a robot. Several teams have worked on the tracking of surgical instruments, based on methods ranging from the development of specific devices to image processing methods. We propose to exploit the instruments' insertion points, which are fixed on the patients abdominal cavity, as a geometric constraint for the localization of the instruments. A simple geometric model of a laparoscopic instrument is described, as well as a parametrization that exploits a spherical geometric grid, which offers attracting homogeneity and isotropy properties. The general architecture of our proposed approach is based on the probabilistic condensation algorithm.

关键词： laparoscopic surgery image-based localization of surgical instruments condensation algorithm

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Modelling of Fish Swimming Patterns Using an Enhanced Object Tracking algorithm

Modelling of Fish Swimming Patterns Using an Enhanced Object...

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2011 International Conference on Frontiers in Computer Education(ICFCE 2011)

作者： Poh Lee Wong Mohd Azam Osman Abdullah Zawawi Talib Khairun Yahya School of Computer Sciences Universiti Sains Malaysia

Modelling of fish swimming patterns has long been a challenge for the aquaculture communityIn this proposed work, the modeling of fish swimming patterns and water condition such as p H, temperature and dissolved oxygen in fish tanks are analysed using network cameras and water sensorsAn enhanced object tracking algorithm consisting of a combination of motion detection and condensation algorithm is applied to detect the change in speed and vector movement of the fishes in the viewing fieldIn addition, this research proposes an intelligent real-time monitoring tool to provide alert signals of water quality and healthy level of fishes.

关键词： fish behaviour swimming pattern motion detection condensation algorithm

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Study of Recognizing Multiple Persons' Complicated Hand Gestures from the Video Sequence Acquired by a Moving Camera

Study of Recognizing Multiple Persons' Complicated Hand Gest...

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Human Vision and Electronic Imaging XV

作者： Dan, Luo Ohya, Jun Waseda Univ Grad Sch Global Informat & Telecommun Studies Honjo Saitama 3670035 Japan

ISBN: (纸本)9780819479204

Recognizing hand gestures from the video sequence acquired by a dynamic camera could be a useful interface between humans and mobile robots. We develop a state based approach to extract and recognize hand gestures from moving camera images. We improved Human-Following Local Coordinate (HFLC) System, a very simple and stable method for extracting hand motion trajectories, which is obtained from the located human face, body part and hand blob changing factor. condensation algorithm and PCA-based algorithm was performed to recognize extracted hand trajectories. In last research, this condensation algorithm based method only applied for one person's hand gestures. In this paper, we propose a principal component analysis (PCA) based approach to improve the recognition accuracy. For further improvement, temporal changes in the observed hand area changing factor are utilized as new image features to be stored in the database after being analyzed by PCA. Every hand gesture trajectory in the database is classified into either one hand gesture categories, two hand gesture categories, or temporal changes in hand blob changes. We demonstrate the effectiveness of the proposed method by conducting experiments on 45 kinds of sign language based Japanese and American Sign Language gestures obtained from 5 people. Our experimental recognition results show better performance is obtained by PCA based approach than the condensation algorithm based method.

关键词： Hand gesture extraction Hand gesture recognition Dynamic camera image condensation algorithm PCA

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Adaptive Real-Time Video-Tracking for Arbitrary Objects

Adaptive Real-Time Video-Tracking for Arbitrary Objects

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Klein, Dominik A. Schulz, Dirk Frintrop, Simone Cremers, Armin B. Univ Bonn Intelligent Vis Syst Grp Dept Comp Sci 3 D-53117 Bonn Germany Fraunhofer FKIE Unmanned Syst Grp D-53343 Wachtberg Germany

ISBN: (纸本)9781424466757

In this paper, we present a visual object tracker for mobile systems that is able to specialize to individual objects during tracking. The core of our method is a novel observation model and the way it is automatically adapted to a changing object and background appearance over time. The model is integrated into the well known condensation algorithm (SIR filter) for statistical inference, and it consists of a boosted ensemble of simple threshold classifiers built upon center-surround Haar-like features, which the filter continuously updates based on the images perceived. We present optimizations and reasonable approximations to limit the computational costs. Thus, the final algorithms are capable of processing video input at real-time. To experimentally investigate the gain of adapting the observation model we compare two different approaches with a non-adapting version of our observation model: maintaining a single observation model for all particles, and maintaining individual observation models for each particle. In addition, experiments were conducted to compare system performances between the proposed algorithms and two other state of the art condensation based tracking approaches.

关键词： adaptive real time video tracking condensation algorithm mobile system nonadapting version object tracking pattern classification threshold classifier video processing visual object tracker

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People detection and tracking with multiple stereo cameras using particle filters

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JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2009年第5期20卷 339-350页

作者： Munoz-Salinas, Rafael Medina-Carnicer, R. Madrid-Cuevas, F. J. Carmona-Poyato, A. Univ Cordoba Dept Comp & Numer Anal E-14071 Cordoba Spain

In this work, a novel approach for people detection and tracking using multiple stereo cameras is proposed. Our proposal consists in combining information from all the available cameras using three different plan-view maps. Occupancy and height maps register the volume and height of the objects that are visible in the stereo cameras, respectively. We also propose the use of a novel map, named confidence map, which registers the confidence of the information projected in each cell. The proposed confidence map is employed to fuse the information captured by each camera so that the most reliable information is kept in each cell. We then propose a particle filter algorithm for tracking people in the fused plan-view maps. The observation model employed considers height, occupancy and confidence information so that information from the most reliable camera is employed at each time instant. The experiments conducted show the validity of our proposal. (C) 2009 Elsevier Inc. All rights reserved.

关键词： Plan-view maps Stereo vision Person tracking Particle filtering Colour processing condensation algorithm Person detection Gesture recognition

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Fingers image tracking on omnidirection camera by condensation algorithm

Fingers image tracking on omnidirection camera by condensati...

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2nd IASTED International Multi-Conference on Automation, Control, and Information Technology

作者： Ikoma, N Sakata, M Doi, M Kyushu Inst Technol Fac Engn Tobata Ku Kitakyushu Fukuoka Japan

ISBN: (纸本)0889864616

Tracking of fingers image on omnidirection camera has been investigated which aims at developing of human friendly interface using fingers' gesture. Where the way of using the omnidirection camera is different from a normal usage in which the user holds the camera with his/her fingers and move them. The interface can use the motion of the fingers to establish a communication between the user and computer system in human friendly way. To achieve this, it is necessary for the system to track the fingers in the dynamic image of omnidirection camera. We have employed condensation algorithm for the tracking. The algorithm uses pre-defined shape of finger called template, and estimates the parameters of affine transformation to adjust the template to the image. The estimation is performed with many number of particles where each particle has an realization of the affine parameters. Applying three steps called prediction, observation, and selection, we have updated particles which approximates a posteriori distribution of the affine parameters given the image sequence up to current time. Real image experiments show the performance of the tracking method.

关键词： onmidirection camera dynamic image finger image tracking condensation algorithm

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A Bayesian plan-view map based approach for multiple-person detection and tracking

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PATTERN RECOGNITION 2008年第12期41卷 3665-3676页

作者： Munoz-Salinas, Rafael Univ Cordoba Dept Computing & Numer Anal E-14071 Cordoba Spain

This work proposes a novel approach for people detection and tracking in colour-with-depth sequences using a particle filtering approach. Detection and tracking are performed in plan-view maps integrating occupancy and height information with a novel plan-view map representation for colour information. Using the three maps, we propose a Multiple particle filtering algorithm for people detection and tracking. The observation model proposed integrates information from the three maps so that people with different coloured clothes are not confused even when they interact at close distances. To avoid the coalescence problem when people with similar coloured clothes approach each other, the weight of particles is modified by an interaction factor that combines colour and position information. The algorithm also avoids the coalescence problem in case of total occlusion by means of an occlusion detection and recovering mechanism. Finally, a solution is proposed to improve the exponential complexity of multiple particle filters so that the algorithm proposed has linear complexity. The approach proposed has been tested in several colour-with-depth sequences where people move and interact freely in the environment. In the sequences, people walk at different distances, cross their paths causing frequent occlusions, jump, run and have close interactions such as shaking hands or embracing each other. The experimental results show that our proposal is able to detect and keep track of every person with a low error and deals with partial and total occlusions. Besides, the detection and tracking techniques presented are appropriate for large tracking problems in real-time applications since their complexity is linear, are suitable for parallel processing and allow the integration of information provided by multiple stereo vision sensors. (C) 2008 Elsevier Ltd. All rights reserved.

关键词： person tracking stereo vision plan-view maps particle filtering colour processing condensation algorithm

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