IEEE Organizations related to Object Tracking

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Conferences related to Object Tracking

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2020 IEEE 23rd International Conference on Information Fusion (FUSION)

The International Conference on Information Fusion is the premier forum for interchange of the latest research in data and information fusion, and its impacts on our society. The conference brings together researchers and practitioners from academia and industry to report on the latest scientific and technical advances.


2020 IEEE International Conference on Image Processing (ICIP)

The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.


ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.


2019 Chinese Control And Decision Conference (CCDC)

Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2018 Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2017 29th Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2016 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create aforum for scientists, engineers and practitioners throughout the world to present the latestadvancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2015 27th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2014 26th Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create aforum for scientists, engineers and practitioners throughout the world to present the latestadvancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2013 25th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2012 24th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2011 23rd Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2010 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies

  • 2009 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2008 Chinese Control and Decision Conference (CCDC)


2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

The IEEE ICCI*CC series is a flagship conference of its field. It not only synergizes theories of modern information science, computer science, communication theories, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software science, knowledge science, cognitive robots, cognitive linguistics, and life science, but also promotes novel applications in cognitive computers, cognitive communications, computational intelligence, cognitive robots, cognitive systems, and the AI, IT, and software industries.

  • 2018 IEEE 17th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Informatics models of the brainCognitive processes of the brainThe cognitive foundation of big dataMachine consciousnessNeuroscience foundations of information processingDenotational mathematics (DM)Cognitive knowledge basesAutonomous machine learningNeural models of memoryInternal information processingCognitive sensors and networksCognitive linguisticsAbstract intelligence (aI)Cognitive information theoryCognitive information fusionCognitive computersCognitive systemsCognitive man-machine communicationCognitive InternetWorld-Wide Wisdoms (WWW+)Mathematical engineering for AICognitive vehicle systems Semantic computingDistributed intelligenceMathematical models of AICognitive signal processingCognitive image processing Artificial neural netsGenetic computingMATLAB models of AIBrain-inspired systemsNeuroinformaticsNeurological foundations of the brainSoftware simulations of the brainBrain-system interfacesNeurocomputingeBrain models

  • 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics is a transdisciplinary field that studies the internal information processing mechanisms of the brain, the underlying abstract intelligence theories and denotational mathematics, and their engineering applications in cognitive computing, computational intelligence, and cognitive systems. Cognitive Computing is a cutting-edge paradigm of intelligent computing methodologies and systems based on CI, which implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. CI and CC not only synergize theories of modern information science, computer science, communication theories, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software science, knowledge science, cognitive robots, cognitive linguistics, and life science, but also reveal exciting applications in cognitive computers, cognitive robots, and computational intelligence.

  • 2016 IEEE 15th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics (CI) is a transdisciplinary field that studies the internal information processing mechanisms of the brain, the underlying abstract intelligence (¿I) theories and denotational mathematics, and their engineering applications in cognitive computing, computational intelligence, and cognitive systems. Cognitive Computing (CC) is a cutting-edge paradigm of intelligent computing methodologies and systems based on cognitive informatics, which implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain.

  • 2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    The scope of the conference covers cognitive informatics, cognitive computing, cognitive communications, computational intelligence, and computational linguitics.

  • 2014 IEEE 13th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive informatics, cognitive computing, cognitive science, cognitive robots, artificial intelligence, computational intelligence

  • 2013 12th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics (CI) is a cutting-edge and multidisciplinary research field that tackles the fundamental problems shared by modern informatics, computing, AI, cybernetics, computational intelligence, cognitive science, intelligence science, neuropsychology, brain science, systems science, software engineering, knowledge engineering, cognitive robots, scientific philosophy, cognitive linguistics, life sciences, and cognitive computing.

  • 2012 11th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive informatics and Cognitive Computing are a transdisciplinary enquiry on the internal information processing mechanisms and processes of the brain and their engineering applications in cognitive computers, computational intelligence, cognitive robots, cognitive systems, and in the AI, IT, and software industries. The 11th IEEE Int l Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 12) focuses on the theme of e-Brain and Cognitive Computers.

  • 2011 10th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)

    Cognitive Informatics and Cognitive Computing are a transdisciplinary enquiry on the internal information processing mechanisms and processes of the brain and their engineering applications in cognitive computers, computational intelligence, cognitive robots, cognitive systems, and in the AI, IT, and software industries. The 10th IEEE Int l Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 11) focuses on the theme of Cognitive Computers and the e-Brain.

  • 2010 9th IEEE International Conference on Cognitive Informatics (ICCI)

    Cognitive Informatics (CI) is a cutting-edge and transdisciplinary research area that tackles the fundamental problems shared by modern informatics, computing, AI, cybernetics, computational intelligence, cognitive science, neuropsychology, medical science, systems science, software engineering, telecommunications, knowledge engineering, philosophy, linguistics, economics, management science, and life sciences.

  • 2009 8th IEEE International Conference on Cognitive Informatics (ICCI)

    The 8th IEEE International Conference on Cognitive Informatics (ICCI 09) focuses on the theme of Cognitive Computing and Semantic Mining. The objectives of ICCI'09 are to draw attention of researchers, practitioners, and graduate students to the investigation of cognitive mechanisms and processes of human information processing, and to stimulate the international effort on cognitive informatics research and engineering applications.

  • 2008 7th IEEE International Conference on Cognitive Informatics (ICCI)

    The 7th IEEE International Conference on Cognitive Informatics (ICCI 08) focuses on the theme of Cognitive Computers and Computational Intelligence. The objectives of ICCI 08 are to draw attention of researchers, practitioners and graduate students to the investigation of cognitive mechanisms and processes of human information processing, and to stimulate the international effort on cognitive informatics research and engineering applications.

  • 2007 6th IEEE International Conference on Cognitive Informatics (ICCI)

  • 2006 5th IEEE International Conference on Cognitive Informatics (ICCI)

  • 2005 4th IEEE International Conference on Cognitive Informatics (ICCI)


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Periodicals related to Object Tracking

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No periodicals are currently tagged "Object Tracking"


Most published Xplore authors for Object Tracking

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Xplore Articles related to Object Tracking

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Pixel based object tracking

2015 2nd International Conference on Signal Processing and Integrated Networks (SPIN), 2015

Number of approaches has been proposed for object tracking in last few years towards increasing performance of computer vision systems. In this paper we propose a tracker which is based on structural information captured in pixels, thus we facilitate a tracker which distinguishes between the target and the background easily. This target-background posterior estimate is further used to track the ...


Particle-Cell Detecting and Tracking in Live-Cell Time-Lapse Images

2017 14th International Symposium on Pervasive Systems, Algorithms and Networks & 2017 11th International Conference on Frontier of Computer Science and Technology & 2017 Third International Symposium of Creative Computing (ISPAN-FCST-ISCC), 2017

Live-cell time-lapse images generated by biological experiments are useful for observing activities, even for proposing novel hypotheses. By identifying particles and cells as objects from live-cell time-lapse images and then tracking the pathways of particles (or cells) to calculate the measures between the particles and cells, such as the distances, they can be quantized for the relationship of particles and ...


Online robust object tracking via a sample-based dynamic dictionary

2013 6th International Congress on Image and Signal Processing (CISP), 2013

We propose an online robust object tracking algorithm based on a sample-based dictionary. The sample-based dictionary in our method means that the over- completely dictionary of sparse coding algorithm is formed by using the sample basis extracted from video images. Different from the other tracking methods that use the object features and a set of boosted classifiers, the proposed algorithm ...


Visual object tracking for handheld devices

2013 IEEE International Symposium on Industrial Electronics, 2013

This paper presents visual object tracking for handheld devices. Due to the low computation performance of handheld devices, the algorithms embedded on the devices are required to be performed with low computational consumption. The usability also should be considered at the same time. We adopted the drag- and-selection method to improve the user interactivity in the target object selection stage. ...


A High Performance Object Tracking Technique with an Adaptive Search Method in Surveillance System

2014 IEEE International Symposium on Multimedia, 2014

In the video scene, the technique on tracking multiple targets, such as tracking group of people through occlusion, is still challenging. In this paper, we present an algorithm for multiple targets tracking system. We discuss the behavior of the moving objects with adaptive search method. Several cases are classified, including the no match case, only-one match case, split case and ...


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Educational Resources on Object Tracking

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IEEE.tv Videos

Control of a Fully-Actuated Airship for Satellite Emulation
Design of Monolithic Silicon-Based Envelope-Tracking Power Amplifiers for Broadband Wireless Applications
RF Power Amplifier Design for Pseudo Envelope Tracking
Learning Control and Knowledge Transfer Between Aerial Robots for Improved Accuracy in Trajectory Tracking
Digital Signal Processing for Envelope Tracking Systems
Handling of a Single Object by Multiple Mobile Robots based on Caster-Like Dynamics
Robotics History: Narratives and Networks Oral Histories: Gary Bradsky
Design Considerations for Wideband Envelope Tracking Power Amplifiers
Envelope Tracking and Energy Recovery Concepts for RF Switch-mode Power Amplifiers
Recording and Using 3D Object Models with RoboEarth
Virtual Reality Support for Teleoperation Using Online Grasp Planning
Computing Conversations: Bertrand Meyer: Eiffel Programming Language
Critical use cases for video capturing systems in autonomous driving applications
CB: Exploring Neuroscience with a Humanoid Research Platform
Michele Nitti: Searching the Social Internet of Things by Exploiting Object Similarity - Special Session on SIoT: WF-IoT 2016
Analytical, Cost & Outcome: POC Testing Implementation - Bradley Karon - IEEE EMBS at NIH, 2019
Finger Mechanism Equipped with Omnidirectional Driving Roller (Omni-Finger)
IEEE WEBINAR SERIES-March 5th, 2014: GaN Crushing Silicon...and Let Me Tell You How
Quadrotor Trajectory Tracking with L1 Optimal control
IROS TV 2019- Pohang University of Science and Technology- Haptics and Virtual Reality Laboratory

IEEE-USA E-Books

  • Pixel based object tracking

    Number of approaches has been proposed for object tracking in last few years towards increasing performance of computer vision systems. In this paper we propose a tracker which is based on structural information captured in pixels, thus we facilitate a tracker which distinguishes between the target and the background easily. This target-background posterior estimate is further used to track the object. It is used for effective tracking of objects in generic computer vision system. It works in heavy occlusion and illumination conditions also. The experimental result shows the effectiveness and success of the tracker during heavy occlusion also it recovers the image sequences from drifts. The approach includes using k-means for creating clusters in order to form the model based on the pixels. The results are encouraging. Furthermore, the proposed algorithm segments the target and background during tracking the objects.

  • Particle-Cell Detecting and Tracking in Live-Cell Time-Lapse Images

    Live-cell time-lapse images generated by biological experiments are useful for observing activities, even for proposing novel hypotheses. By identifying particles and cells as objects from live-cell time-lapse images and then tracking the pathways of particles (or cells) to calculate the measures between the particles and cells, such as the distances, they can be quantized for the relationship of particles and cells. Various tools of particle or cell tracking have been proposed. However, there is no famous tool has been proposed to achieve the above goals. Hence, in order to accomplish the purposes, a particle-cell relation mining method, abbreviate to PCRM, has been proposed here. In the PCRM method, there are four phases: object identification, objects tracking, measures calculation, and relation mining. By using the PCRM method, the relationship between particles and cells has tried to be found in this paper, and the PCRM method is useful for biologists to prove their hypotheses.

  • Online robust object tracking via a sample-based dynamic dictionary

    We propose an online robust object tracking algorithm based on a sample-based dictionary. The sample-based dictionary in our method means that the over- completely dictionary of sparse coding algorithm is formed by using the sample basis extracted from video images. Different from the other tracking methods that use the object features and a set of boosted classifiers, the proposed algorithm considers the raw image patches around the object as basis vectors and the maximum a posteriori is used to decide the object position in the next frame. Our method is simple for the dictionary that is updated automatically and the object is updated to alleviate the visual drift problem in every frame without learning process, which needs much time consuming. Experiments are conducted on the challenging sequences to demonstrate that the proposed method is fast and effective. The results show that the proposed method outperforms the current state-of-the-art methods.

  • Visual object tracking for handheld devices

    This paper presents visual object tracking for handheld devices. Due to the low computation performance of handheld devices, the algorithms embedded on the devices are required to be performed with low computational consumption. The usability also should be considered at the same time. We adopted the drag- and-selection method to improve the user interactivity in the target object selection stage. To implement this method, we used flood-fill algorithm. In the main tracking process, we select mean-shift tracking as a main tracking algorithm. As a feature of mean-shift, we used color-based histogram backprojection. Additionally, the overall algorithm is modified for improving the speed of the tracking process. We validated the algorithm on the handheld device with low computation power and tested in several real situations.

  • A High Performance Object Tracking Technique with an Adaptive Search Method in Surveillance System

    In the video scene, the technique on tracking multiple targets, such as tracking group of people through occlusion, is still challenging. In this paper, we present an algorithm for multiple targets tracking system. We discuss the behavior of the moving objects with adaptive search method. Several cases are classified, including the no match case, only-one match case, split case and occlusion case respectively. With this system, we can track the moving people in successive frame by object boundary box and velocity without color cues or appearance model. Even though people are interacted with each other or the occlusion is caused by other foreground objects, the proposed algorithm can still perform well. Furthermore we consider the people movement with respect to the distance with the camera as an adaptive search range to deal with the condition. As the foreground is similar to the background, the proposed algorithm can still solve the problem on the detection error.

  • A new real-time robust object tracking method

    In this paper, we propose a real-time robust object tracking method that is based on a generative visual appearance model but with some level of background awareness. We introduce several strategies to ensure a stable visual appearance model for the target as tracking progresses. The strategies include modeling of a foreground color distribution, maintaining a set of foreground templates with the target region emphasized, and incorporating background templates into the dictionary for sparse representation of the target appearance. Experimental results demonstrate that our method outperforms several latest state-of-the-art tracking methods in terms of tracking performance.

  • First-person multiple object tracking in complex traffic scenes

    In this paper, we study multi-object tracking problem from the first-person viewpoint, e.g., the moving camera. This problem is different from the traditional one with static camera and brings lots of challenges. To solve this problem, we adopt the tracking-by-detection approach and design a new similarity model for two detection responses considering the camera motion. The similarity model can handle the change of scale and position of objects under the movement of camera. We also consider the detection prior and appearance to improve the tracking performance. The final tracking problem is solved within a network flow framework. Experimental results on KITTI dataset demonstrate the advantages of our method.

  • Online multiple object tracking with the hierarchically adopted GM-PHD filter using motion and appearance

    This paper presents an online multiple object tracking (MOT) method based on tracking by detection. Tracking by detection has the inherent problems by false and miss detection. To deal with the false detection, we employed the Gaussian mixture probability hypothesis density (GM-PHD) filter because this filter is robust to noisy and random data processing containing many false observations. Thus, we revised the GM-PHD filter for visual MOT. Also, to handle miss detection, we propose a hierarchical tracking framework to associate fragmented or ID switched tracklets. Experiments with the representative dataset PETS 2009 S2L1 show that our framework are effective to decrease the errors by false and miss detection, and real-time capability.

  • Track fast-moving tiny flies by adaptive LBP feature and cascaded data association

    Studying the behavior of fruit flies that mimic normal animal motivations can inform us about the molecular mechanisms and biochemical pathways. We build a glass chamber to house flies and record their behaviors in video frame sequences. Due to the challenges of low image contrast, small object size and fast object motion, we propose an adaptive Local Binary Pattern (LBP) feature to detect flies and develop a cascaded data association approach with fine-to- coarse gating region control to track flies in the spatio-temporal domain. Our approach is validated on two long video sequences with very good performance, showing its potential to enable automated characterization of biological processes.

  • Determining direction of moving object using object tracking for smart weelchair controller

    People with disabilities who cannot move their whole body need other people to control the smart wheelchair or track the moving of object interest, in this case people. In this paper, we have proposed new movement controller of smart wheelchair using object tracking for disabled people who cannot move their whole body. The proposed method for determining direction of moving object using object tracking has been evaluated using invariant video. Our result study have success rate of multiple object detection is 82.01%, tracking object interest is 90.00%, and determining the moving object directions is 79.63%.



Standards related to Object Tracking

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Jobs related to Object Tracking

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