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11th International Multi-Conference on Systems, Signals and Devices (SSD)

作者： Aguilar, Wilbert G. Angulo, Cecilio UPC BarcelonaTech Dept Automat Control Barcelona Spain

ISBN: (纸本)9781479938667

Currently, different hand-held devices as domestic cameras, smart-phones, tablets, or on-board cameras for robots are becoming popular for video capturing. A main concern with these gadgets is undesired movement between consecutive frames. Video stabilization is a technique with increasing impact for solving this problem. In this paper, a proposal is introduced for robust video stabilization, in particular for on-board cameras in micro aerial vehicles. It is based on a combination of the ransac (RANdom SAmple Consensus) algorithm and gray level differences as cost function for local motion parameter estimation, as well as a low-pass filter for global motion smoothing. Experimentation will illustrate about of the robustness proposed solution.

关键词： autonomous aerial vehicles cameras image motion analysis microrobots mobile robots robot vision smart phones video signal processing ransac algorithm cost function domestic cameras global motion smoothing local motion parameter estimation low-cost microaerial vehicles low-pass filter motion intention on-board cameras random sample consensus algorithm robust video stabilization smart-phones tablets video capturing Cameras Cost function Estimation Mathematical model Motion estimation Robot vision systems Robustness

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A Methodology of Vehicle Speed Estimation Based on Optical Flow

A Methodology of Vehicle Speed Estimation Based on Optical F...

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IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)

作者： Xu Qimin Li Xu Wu Mingming Li Bin Song Xianghui Southeast Univ Sch Instrument Sci & Engn Nanjing 210096 Jiangsu Peoples R China Minist Transport Res Inst Highway Beijing 100088 Peoples R China

ISBN: (纸本)9781479960583

It has great significance to acquire vehicle speed for active safety system. This paper presents a methodology for identifying vehicle speed by obtaining a sparse optical flow from image sequences. Distinct corners can be detected by Harris corner detector after image enhancement. Then, Lucas-Kanade method for optical flow calculation is utilized to match the sparse feature set of one frame on the consecutive frame. In order to improve the accuracy of optical flow, ransac algorithm is introduced to optimize the matched corners. Finally, the vehicle speed can be determined by averaging all the speeds estimated by every optimized matched corner. The results of field test indicated that the computation time of the developed method to execute for one time was 59ms, and the mean error of speed estimation relative to the measurement of GPS was 0.121 m/s. The developed method can achieve satisfying performance, such as accuracy and output frequency.

关键词： Global Positioning System edge detection estimation theory image enhancement image sequences road safety traffic engineering computing vehicles GPS Harris corner detector Lucas-Kanade method ransac algorithm active safety system optical flow vehicle speed estimation Adaptive optics Computational modeling Integrated optics Optical imaging Optical sensors Optimization Q measurement Global Positioning Systems image sequences Optic Flow image enhancement Active safety systems Q measurement Vehicle speed Speed Estimation estimation theory adaptive optics optical sensors Integrated optics Optical Imaging Road safety Computational modeling

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Automatic Needle Detection and Tracking in 3D Ultrasound Using an ROI-Based ransac and Kalman Method

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ULTRASONIC IMAGING 2013年第4期35卷 283-306页

作者： Zhao, Yue Cachard, Christian Liebgott, Herve Univ Lyon INSA Lyon CNRS UMR5220 CREATISINSERMU1044 F-69622 Villeurbanne France

This article proposes a robust technique for needle detection and tracking using three-dimensional ultrasound (3D US). It is difficult for radiologists to detect and follow the position of micro tools, such as biopsy needles, that are inserted in human tissues under 3D US guidance. To overcome this difficulty, we propose a method that automatically reduces the processed volume to a limited region of interest (ROI), increasing at the same time the calculation speed and the robustness of the proposed technique. First, a line filter method that enhances the contrast of the needle against the background is used to facilitate the initialization of ROI using the tubularness information of the complete US volume. Then, the random sample consensus (ransac) and Kalman filter (RK) algorithm is used in the ROI to detect and track the precise position of the needle. A series of numerical inhomogeneous phantoms with a needle simulated from real 3D US volumes are used to evaluate our method. The results show that the proposed method is much more robust than the ransac algorithm when detecting the needle, regardless of whether or not the insertion axis corresponds to an acquisition plane in the 3D US volume. The possibility of failure is also discussed in this article.

关键词： ransac algorithm Kalman filter line filter motion estimation 3D ultrasound

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Surface fitting for individual image thresholding and beyond

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IET IMAGE PROCESSING 2013年第6期7卷 596-605页

作者： Cai, Jinhai Miklavcic, Stan Univ S Australia Phen & Bioinformat Res Ctr Adelaide SA 5095 Australia Univ Adelaide Plant Genom Ctr Australian Ctr Plant Funct Genom Urrbrae SA 5064 Australia

In this study, the authors propose a novel algorithm for background-foreground segmentation. The work is motivated by the need for information about the background that is obscured by objects, in order to achieve accurate segmentation. The algorithm utilises the principle of estimating the occluded background by surface fitting. Edge detection methods are used to detect boundaries between foreground and background, identifying background points as well as foreground points. This categorisation will guarantee that most points used for surface fitting are from the same category and thus the proposed surface fitting with random sample consensus (ransac) algorithm will produce an accurate estimate of the surface. The authors algorithm has been applied to the real-world applications of segmenting plant images with inhomogeneous but smooth background and measuring the relative temperature of plants. Comparisons with experimental results show that the proposed algorithm is able to reduce significantly background inhomogeneities in infra-red images for the accurate estimation of temperature differences between background and plants, which provides important clues for fast and cheap genetic screening. The proposed algorithm is also able to overcome the intensity inhomogeneities for accurate image segmentation, particularly for plant root image segmentation with the preservation of lateral plant roots.

关键词： botany curve fitting edge detection image segmentation infrared imaging temperature measurement surface fitting image thresholding backgroundaEuro"foreground segmentation occluded background estimation edge detection boundary detection ransac algorithm temperature measurement infrared image temperature difference estimation plant root image segmentation

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Sensor Data Fusion algorithm for Indoor Environment Mapping Using Low-Cost Sensors

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JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS 2013年第3期24卷 199-211页

作者： Buonocore, Luciano Nascimento Junior, Cairo Lucio Neto, Areolino de Almeida Univ Fed Maranhao Dept Engn Eletricidade BR-65085581 Sao Luis MA Brazil Inst Tecnol Aeronaut Div Engn Eletron BR-12228900 Sao Jose Dos Campos SP Brazil

This article is concerned with 2D indoor environment mapping produced by a sensor data fusion algorithm. Ameasurement subsystem assembled on a mobile robot uses its sensors to gather data from its surroundings. In this article, an algorithm is proposed and evaluated to fuse data acquired by the following low-cost sensors: a visual sensor (a wireless webcam with a laser pointer) and three range finder sensors (two infrared units and a sonar transducer). The main steps of the proposed solution are: (a) at each accurate robot pose an occupancy grid (OG) probabilistic map is generated for each type of sensor, (b) the three OG maps are merged using competitive fusion and the ransac algorithm is employed to extract line segments, (c) the line segments are further processed using competitive and/or complementary fusion resulting in a feature-based map for each robot pose. The previous steps are repeated until all robots pose are computed. The feature-based maps for all robot poses are then merged using competitive fusion, and a final precise OG map of the environment is generated. The proposed algorithm was evaluated using data gathered by the SLAMVITA robot sensors in two small test environments. The experimental results have shown that the proposed algorithm was able to build precise maps of the test environments (error less than 1.5%).

关键词： Sensor data fusion Visual sensor Low-cost sensors Probabilistic mapping ransac algorithm

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FAST OBJECT RE-DETECTION AND LOCALIZATION IN VIDEO FOR SPATIO-TEMPORAL FRAGMENT CREATION

FAST OBJECT RE-DETECTION AND LOCALIZATION IN VIDEO FOR SPATI...

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IEEE International Conference on Multimedia and Expo Workshops (ICMEW)

作者： Apostolidis, Evlampios Mezaris, Vasileios Kompatsiaris, Ioannis Ctr Res & Technol Hellas Inst Informat Technol Thermi 57001 Greece

ISBN: (纸本)9781479916030

This paper presents a method for the detection and localization of instances of user-specified objects within a video or a collection of videos. The proposed method is based on the extraction and matching of SURF descriptors in video frames and further incorporates a number of improvements so as to enhance both the detection accuracy and the time efficiency of the process. Specifically, (a) GPU-based processing is introduced for specific parts of the object re-detection pipeline, (b) a new video-structure-based sampling technique is employed for limiting the number of frames that need to be processed and (c) improved robustness to scale variations is achieved by generating and employing additional instances of the object of interest based on the one originally provided by the user. The experimental results show that the algorithm achieves high levels of detection accuracy while the overall needed processing time makes the algorithm suitable for quick instance-based labeling of video and the creation of object-based spatio-temporal fragments.

关键词： Object Re-detection SURF descriptors ransac algorithm Shot Segmentation GPU processing

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Indoor navigation assistance with a Smartphone camera based on vanishing points

Indoor navigation assistance with a Smartphone camera based ...

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International Conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Elloumi, Wael Guissous, Kamel Chetouani, Aladine Canals, Raphael Leconge, Remy Emile, Bruno Treuillet, Sylvie Univ Orleans Lab PRISME F-45067 Orleans France

ISBN: (纸本)9781479940431

Indoor navigation assistance is a highly challenging task that is increasingly needed in various types of applications such as visually impaired guidance, emergency intervention, tourism, etc. Many alternative techniques to GPS have been explored to deal with this challenge like pre-installed sensor networks (Wifi, Ultra Wide Band, Bluetooth, Radio Frequency IDentification etc), inertial sensors or camera. This paper presents an indoor navigation system on Smartphone that was designed taking into consideration low cost, portability and the lightweight of the used algorithm in terms of computation power and storage space. The proposed solution relies on embedded vision. Robust and fast camera orientation (3 dot) is estimated by tracking three orthogonal vanishing points in a video stream acquired with the camera of a free-handled Smartphone. The developed algorithm enables indoor pedestrian localization in two steps: an off-line learning step defines a reference path by selecting key frames along the way using saliency extraction method and computing the camera orientation in these frames. Then, in localization step, an approximate but realistic position of the walker is estimated in real time by comparing the orientation of the camera in the current image and that of reference to assist the pedestrian with navigation guidance. Unlike SLAM, this approach does not require to build 3D mapping of the environment. Online walking direction is given by Smartphone camera which advantageously replaces the compass sensor since it performs very poorly indoors due to electromagnetic noise. Experiments, executed online on Smartphone, that show the feasibility and evaluate the accuracy of the proposed positioning approach for different indoor paths.

关键词： navigation assistance vanishing points real-time camera orientation ransac algorithm smartphone

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Salient Object Detection in Video Streams

Salient Object Detection in Video Streams

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10th International Symposium on Electronics and Telecommunications (ISETC)

作者： Tapu, Ruxandra Mocanu, Bogdan Tapu, Ermina Univ Politehn Bucuresti Dept Telecommun Fac ETTI Bucharest Romania Univ Politehn Bucuresti Fac Aerosp Engn Dept Descript Geometry & Engn Graph Bucharest Romania

ISBN: (纸本)9781467311762

In this paper we propose a complete framework for automatic detection and tracking of salient objects in video streams. The video flow is firstly segmented into shots based on scale space filtering graph partition method. For each detected shot the associated static summary is developed using a leap keyframe extraction method. Based on the representative images we introduce next a combined spatial and temporal video attention model that is able to recognize both interesting objects and actions in image sequences. The approach extends the state-of-the-art image region based contrast saliency with a temporal attention model. Different types of motion presented in the current shot are determined using a set of homographic transforms, estimated by recursively applying the ransac algorithm on the interest point correspondence. Finally, a decision is taken based on the combined information from both saliency maps. The experimental results validate the proposed framework and demonstrate that our approach is suitable for various types of videos and is robust to noise and low resolution.

关键词： Salient map temporal attention model homography transform ransac algorithm

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VIDEO STRUCTURING: FROM PIXELS TO VISUAL ENTITIES

VIDEO STRUCTURING: FROM PIXELS TO VISUAL ENTITIES

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20th European Signal Processing Conference (EUSIPCO)

作者： Tapu, Ruxandra Zaharia, Titus CNRS Inst Mines Telecom Telecom SudParis ARTEMIS Dept UMR MAP5 8145 F-91000 Evry France

ISBN: (纸本)9781467310680

In this paper we propose a method for automatic structuring of video documents. The video is firstly segmented into shots based on a scale space filtering graph partition method. For each detected shot the associated static summary is developed using a leap key-frame extraction method. Based on the representative images obtained, we introduce next a combined spatial and temporal video attention model that is able to recognize moving salient objects. The proposed approach extends the state-of-the-art image region based contrast saliency with a temporal attention model. Different types of motion presented in the current shot are determined using a set of homographic transforms, estimated by recursively applying the ransac algorithm on the interest point correspondence. Finally, a decision is taken based on the combined spatial and temporal attention models. The experimental results validate the proposed framework and demonstrate that our approach is effective for various types of videos, including noisy and low resolution data.

关键词： Saliency maps temporal attention model homography transform ransac algorithm

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A Drug Administration Decision Support System

A Drug Administration Decision Support System

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IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： You, Wenqi Simalatsar, Alena Widmer, Nicolas De Micheli, Giovanni Ecole Polytech Fed Lausanne Integrated Syst Lab CH-1015 Lausanne Switzerland Univ Lausanne Ctr Hosp CH-1015 Lausanne Switzerland

ISBN: (纸本)9781467327466;9781467327459

Drug delivery is one of the most common clinical routines in hospitals, and is critical to patients' health and recovery. It includes a decision making process in which a medical doctor decides the amount (dose) and frequency (dose interval) on the basis of a set of available patients' feature data and the doctor's clinical experience (a priori adaptation). This process can be computerized in order to make the prescription procedure in a fast, objective, inexpensive, non-invasive and accurate way. This paper proposes a Drug Administration Decision Support System (DADSS) to help clinicians/patients with the initial dose computing. The system is based on a Support Vector Machine (SVM) algorithm for estimation of the potential drug concentration in the blood of a patient, from which a best combination of dose and dose interval is selected at the level of a DSS. The addition of the RANdom SAmple Consensus (ransac) technique enhances the prediction accuracy by selecting inliers for SVM modeling. Experiments are performed for the drug imatinib case study which shows more than 40% improvement in the prediction accuracy compared with previous works. An important extension to the patient features' data is also proposed in this paper.

关键词： Decision Support System Support Vector Machine ransac algorithm

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