Motion Blurbased State Estimation

• doi: 10.1109/TCST.2015.2473004
• title: Motion Blur-Based State Estimation
• publisher: IEEE
• isbn:
• issn: 2374-0159
• rank: 3050
• access_type: LOCKED
• content_type: Journals
• abstract: Motion measurement increasingly deploys image sensors such as charge-coupled device and CMOS arrays, driven by their ever-improving resolution, response time, noise level, and cost. The typical usage is to operate an image sensor and the associated optics as a sampler, by taking a series of high-speed sharp pictures to infer motion. Image blur is treated as an undesirable artifact, to be removed using shorter exposure times or image processing techniques such as deblurring. We have previously shown that dynamic information embedded in image blur may be exploited for model identification in frequency ranges well beyond the Nyquist frequency. In this brief, we investigate the state estimation problem using motion blur. We pose the problem as a minimization, estimating the state at the start of each (slow) sampling period based on the observed motion blur. We show that the local convexity of the minimization corresponds to a generalized observability criterion. This method is compared with other techniques, including the conventional centroid-based method, and that based on the use of multiple image moments. The simulation and experimental results demonstrate the fast response and robustness of the proposed scheme in the presence of synthetic stray light.
• article_number: 7271044
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7271044
• html_url: https://ieeexplore.ieee.org/document/7271044/
• abstract_url: https://ieeexplore.ieee.org/document/7271044/
• publication_title: IEEE Transactions on Control Systems Technology
• conference_location:
• conference_dates:
• publication_number: 87
• is_number: 7454797
• publication_year: 2016
• publication_date: May 2016
• start_page: 1012
• end_page: 1019
• citing_paper_count: 6
• citing_patent_count: 0
• download_count: 451
• insert_date: 20150917
• index_terms:
  • ieee_terms:
    • Image sensors
    • Kernel
    • State estimation
    • Convergence
    • Minimization
    • Sensors
  • author_terms:
    • Adaptive optics
    • image-based control
    • image sensors
    • motion blur
    • multirate
    • state estimation
    • visual servoing
    • Adaptive optics
    • image-based control
    • image sensors
    • motion blur
    • multirate
    • state estimation
    • visual servoing
  • dynamic_index_terms:
    • CCD Camera
    • Charge-coupled Device
    • Image Sensor
    • Camera Sensor
    • Motion Blur
    • Blurred Images
    • Present Scheme
    • State Estimation Problem
    • Deblurring
    • Locally Convex
    • Undesirable Artifacts
    • Undesirable Artefacts
    • Image Moments
    • Moment Invariants
    • Dynamical
    • Slower Rate
    • Intensity Distribution
    • Volume Of Distribution
    • Minimization Problem
    • Second Moment
    • Statistical Moments
    • Charge-coupled Device Camera
    • Sensor Measurements
    • Angular Position
    • Angular Direction
    • Moments Of Distribution
    • Steady-state Error
    • Kernel Images
    • Operating System Kernel
    • Kernel Design
    • OS Kernel
    • Pixel Domain
    • Local Convergence
    • Fast Step
    • Exposure Window
    • Beginning Of Step
    • Beginning Of Each Step
    • Integral Transform
    • Alternative Metrics
    • Surrogate Metrics
    • State Estimation Error
    • Linear Time-invariant
• authors:
  • Author Name: Jacopo Tani
    Affiliation: Mechanical, Aerospace, and Nuclear Engineering Department, Rensselaer Polytechnic Institute, Troy, NY, USA
    Author URL: https://ieeexplore.ieee.org/author/38548446100
    ID: 38548446100
    Order: 1
    Author Affiliations:
    • Mechanical, Aerospace, and Nuclear Engineering Department, Rensselaer Polytechnic Institute, Troy, NY, USA
  • Author Name: Sandipan Mishra
    Affiliation: Mechanical, Aerospace, and Nuclear Engineering Department, Rensselaer Polytechnic Institute, Troy, NY, USA
    Author URL: https://ieeexplore.ieee.org/author/37532698000
    ID: 37532698000
    Order: 2
    Author Affiliations:
    • Mechanical, Aerospace, and Nuclear Engineering Department, Rensselaer Polytechnic Institute, Troy, NY, USA
  • Author Name: John T. Wen
    Affiliation: Industrial and Systems Engineering Department, Rensselaer Polytechnic Institute, Troy, NY, USA
    Author URL: https://ieeexplore.ieee.org/author/37278935000
    ID: 37278935000
    Order: 3
    Author Affiliations:
    • Industrial and Systems Engineering Department, Rensselaer Polytechnic Institute, Troy, NY, USA

Image Sensor

• sensor_type: CMOS
• resolution: Not specified in the paper
• dynamic_range: Not specified in the paper
• pixel_size: Not specified in the paper
• dark_current: Not specified in the paper

Optical Data

• focal_length: Not specified in the paper
• aperture: Not specified in the paper
• field_of_view: Not specified in the paper
• distortion: Not specified in the paper

Performance Metrics

• frame_rate: Not specified in the paper
• signal_to_noise_ratio: Not specified in the paper
• sensitivity: Not specified in the paper
• shutter_speed: Not specified in the paper
• power_consumption: Not specified in the paper
• noise: Not specified in the paper

Applications & Benefits

• cell_imaging: Not specified in the paper
• benefits: Enabled digital imaging in a variety of applications such as smartphones, medical devices, and automotive systems.

Supporting Organizations

• supported_by: National Science Foundation, Smart Lighting Engineering Research Center, Center for Automation Technologies and Systems

Manuscript Details

• publication_date: May 2016

Relevancy Score

• score: 8
• missing_fields:
  • resolution
  • dynamic_range
  • pixel_size
  • dark_current
  • focal_length
  • aperture
  • field_of_view
  • distortion
  • frame_rate
  • signal_to_noise_ratio
  • sensitivity
  • shutter_speed
  • power_consumption
  • noise

Processed JSON Filename

request_8353c71d-3237-4840-b92e-51b32ad7d299-motion_blurbased_state_estimation.json