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A probabilistic object tracking model based on condensation algorithm

SOFT COMPUTING 2014年第12期18卷 2425-2430页

作者： Catak, Muammer Izmir Univ Dept Elect & Commun Engn Izmir Turkey

Object tracking, which has many application in our daily life, is an important topic in electronics engineering area. It basically deals with estimation and location of an object in given video frames. In this paper, a novel object tracking algorithm based on particle filtering associate with population balances is proposed. The developed algorithm was used to track objects in synthetic frames and natural video frames. According to results, it has high accuracy level for single and multi-object tracking.

关键词： condensation algorithm Variance reduction Object tracking Population balances

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Mining Method for Road Traffic Network Synchronization Control Area 7th

Mining Method for Road Traffic Network Synchronization Contr...

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7th International Conference on Green Intelligent Transportation System and Safety (GITSS)

作者： Zheng, Lili Liu, Hu Ding, Tongqiang Xing, Ruru Hu, Xinyue Jilin Univ State Key Lab Automobile Simulat & Control Changchun 130022 Jilin Peoples R China Jilin Univ Coll Transportat Changchun 130022 Jilin Peoples R China Jilin Univ Jilin Prov Key Lab Rd Traff Changchun 130022 Jilin Peoples R China

ISBN: (纸本)9789811035517;9789811035500

To ensure the road network synchronization control effect, it needs the correct division of synchronous control area. Therefore, according to the topology and traffic flow characteristics of road traffic network, this paper constructs road network modularity based on weights which are defined by the correlation degree between the intersections and designs synchronization control zoning method with the goal of maximizing modularity. At the same time, this paper uses road topology, traffic flow data, and tidal characteristics of the morning and evening peak time of business district of Guilin Road in Changchun and apples MATLAB and VISSIM to verify the analysis. The results show that the method is feasible and effective.

关键词： Road traffic network modularity The key node condensation algorithm

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Assisted Navigation for Persons with Reduced Mobility: Path Recognition Through Particle Filtering (condensation algorithm)

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2010年第1期60卷 19-57页

作者： Grasse, Regis Morere, Yann Pruski, Alain Univ Paul Verlaine Metz LASC F-57012 Metz 1 France

In the few past decades, several international researchers have worked to develop intelligent wheelchairs for the people with reduced mobility. For many of these projects, the structured set of commands is based on a sensor-based command. Many types of commands are available but the final decision is to be made by the user. A former work established a behaviour-based multi-agent form of control ensuring that the user selects the best option for him/her in relation to his/her preferences or requirements. This type of command aims at "merging" this user and his/her machine-a kind of symbiotic relationship making the machine more amenable and the command more effective. In this contribution, the approach is based on a curve matching procedure to provide comprehensive assistance to the user. This new agent, using a modelization of the paths that are most frequently used, assists the user during navigation by proposing the direction to be taken when the path has been recognized. This approach will spare the user the effort of determining a new direction-which might be a major benefit in the case of severe disabilities. The approach considered uses particle filtering to implement the recognition of the most frequent paths according to a topological map of the environment.

关键词： Assistance to navigation Particle filtering condensation algorithm Course modelling Recognition Smart wheelchair

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A computationally efficient importance sampling tracking algorithm

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MACHINE VISION AND APPLICATIONS 2014年第7期25卷 1761-1777页

作者： Farah, Rana Gan, Qifeng Langlois, J. M. Pierre Bilodeau, Guillaume-Alexandre Savaria, Yvon Ecole Polytech Comp & Software Engn Dept Montreal PQ H3C 3A7 Canada Ecole Polytech Dept Elect Engn Montreal PQ H3C 3A7 Canada

This paper proposes a computationally efficient importance sampling algorithm applicable to computer vision tracking. The algorithm is based on the condensation algorithm, but it avoids expensive operations that are costly in real-time embedded systems. It also includes a method that reduces the number of particles during execution and a new resampling scheme. Our experiments demonstrate that the proposed algorithm is as accurate as the condensation algorithm. Depending on the processed sequence, the acceleration with respect to condensation can reach 7 for 50 particles, 12 for 100 particles and 58 for 200 particles.

关键词： Video tracking condensation algorithm Particle filter

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Externally Navigated Bronchoscopy Using 2-D Motion Sensors: Dynamic Phantom Validation

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IEEE TRANSACTIONS ON MEDICAL IMAGING 2013年第10期32卷 1745-1764页

作者： Luo, Xiongbiao Kitasaka, Takayuki Mori, Kensaku Nagoya Univ Informat & Commun Headquarters Nagoya Aichi 4648603 Japan Aichi Inst Technol Fac Informat Sci Toyota Aichi 47003 Japan

The paper presents a new endoscope motion tracking method that is based on a novel external endoscope tracking device and our modified stochastic optimization method for boosting endoscopy navigation. We designed a novel tracking prototype where a 2-D motion sensor was introduced to directly measure the insertion-retreat linear motion and also the rotation of the endoscope. With our developed stochastic optimization method, which embeds traceable particle swarm optimization in the condensation algorithm, a full six degrees-of-freedom endoscope pose (position and orientation) can be recovered from 2-D motion sensor measurements. Experiments were performed on a dynamic bronchial phantom with maximal simulated respiratory motion around 24.0 mm. The experimental results demonstrate that our proposed method provides a promising endoscope motion tracking approach with more effective and robust performance than several current available tracking techniques. The average tracking accuracy of the position improved from 6.5 to 3.3 mm, which further approaches the clinical requirement of 2.0 mm in practice.

关键词： condensation algorithm endoscopy navigated bronchoscopy optical mouse senor particle swarm optimization stochastic optimization methods three-dimensional (3-D) motion tracking two-dimensional (2-D) motion sensor

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Appearance-Based Subspace Learning Model Using Incremental PCA in Object Tracking 3

Appearance-Based Subspace Learning Model Using Incremental P...

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3rd International Conference on Computer Science and Network Technology (ICCSNT)

作者： Wu Gang Zhang Haofeng Nanjing Inst Technol Sch Automot & Rail Transit Nanjing 211167 Jiangsu Peoples R China Nanjing Univ Sci & Technol Sch Comp Sci & Technol Nanjing 210094 Jiangsu Peoples R China

ISBN: (纸本)9781479905614

Visual tracking is still a challenging subject due to the targeted object's change in direction and size, stochastic disturbance, and drastic lighting change under complicated scene. Based on the subspace' updating and real-time learning, a visual tracking framework is proposed in the work. The Incremental PCA algorithm and the new measurement on subspace's similarity in computing particles' weights are introduced in our tracking processes under condensation algorithm. Not based on the trained database in advance, our method updates the subspace about the moving target by continuously discarding the old frame and adopting the new one. Differed from conventional PCA method, the Incremental PCA method adaptively updates the subspace which can reflect appearance variation of the moving target over long period of time. Compared with condensation algorithm using color histogram, the tracker proposed in this paper can effectively track the target under complicated surrounding and it is being incrementally updated with new frames. Challenging experimentations on standard testing videos demonstrate the proposed tracker's effectiveness and accurateness in actual tracking processes.

关键词： Visual tracking condensation algorithm Subspace Incremental PCA

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Particle filtering in the Hough space for instrument tracking

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COMPUTERS IN BIOLOGY AND MEDICINE 2012年第5期42卷 614-623页

作者： Climent, Joan Hexsel, Roberto A. Univ Fed Parana Depto Informat BR-80060000 Curitiba Parana Brazil Tech Univ Catalonia Dept Comp Engn Barcelona Spain

In this paper we present a real-time tracking system of surgical instruments in laparoscopic operations. We combine condensation tracking, with the Hough Transform in order to obtain an efficient and accurate tracking. The condensation algorithm performs well in heavy clutter, and the Hough Transform is robust under illumination changes, occlusion and distractions. The Hough array is computed using the gradient direction image obtained by means of a Principal Component Analysis. This improves accuracy in the determination of edge orientation and speeds up computation of the Hough Transform. The experiments on image sequences of actual laparoscopic surgical operations show that the instrument tip is located even in the presence of smoke, occlusions or motion blurring. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Instrument tracking Laparoscopic surgery Principal Components Analysis Hough Transform condensation algorithm

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Shape from pairwise silhouettes for plan-view map generation

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IMAGE AND VISION COMPUTING 2012年第2期30卷 122-133页

作者： Munoz-Salinas, Rafael Yeguas-Bolivar, E. Diaz-Mas, L. Medina-Carnicer, Rafael Univ Cordoba Dept Comp & Numer Anal E-14071 Cordoba Spain

A plan-view map is a representation mechanism especially appropriated for people detection and tracking. It allows to represent volumetric information in a very compact and efficient way so that very effective detection and tracking algorithms can be applied using it. In spite of their advantages, plan-view maps have mainly been used with stereo cameras but not with monocular ones. The reason why is that many of the three-dimensional reconstruction algorithms using monocular vision impose strong conditions (such as controlled lightning, lack of occlusion, etc.) thus impeding their applicability in realistic environments. This paper presents two main novelties. First, a three-dimensional reconstruction algorithm that is especially appropriate for people detection and tracking because of its robustness to errors in the background subtraction. Second, a new technique for creating plan-view maps from volumetric reconstructions that reduces the amount of false positives in the occluded regions. We show experimentally that these techniques produce plan-view maps that can be reliably employed for tracking purposes. The proposed methods are compared with the traditional SfS obtaining relevant improvements. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Plan-view maps Shape from silhouettes Person tracking Particle filtering Color processing 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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International Conference on Frontiers in Computer Education (ICFCE 2011)

作者： Wong, Poh Lee Osman, Mohd Azam Talib, Abdullah Zawawi Yahya, Khairun Univ Sains Malaysia Sch Comp Sci Usm 11800 Penang Malaysia Univ Sains Malaysia CEMACS George Town 11800 Malaysia

ISBN: (纸本)9783642275517

Modelling of fish swimming patterns has long been a challenge for the aquaculture community. In this proposed work, the modeling of fish swimming patterns and water condition such as pH, temperature and dissolved oxygen in fish tanks are analysed using network cameras and water sensors. An 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 field. In 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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Human Gesture Analysis using Multimodal features

Human Gesture Analysis using Multimodal features

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Dan, Luo Ekenel, Hazim Kemal Jun, Ohya Waseda Univ Grad Sch Global Informat & Telecommun Studies Multimedia Sci Tokyo Japan Karlsruhe Inst Technol Dept Comp Sci Karlsruhe Germany

ISBN: (纸本)9780769547299

Human 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 PLS 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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