Gesture Recognition Using Fpga And Ov7670 Camera

• doi: 10.1109/ICISC.2017.8068593
• title: Gesture recognition using FPGA and OV7670 camera
• publisher: IEEE
• isbn: 978-1-5090-4716-1
• issn:
• rank: 2544
• access_type: LOCKED
• content_type: Conferences
• abstract: Gesture recognition has lured everyone's attention as a new generation of HCI and visual input mode. FPGA presents a better overall performance and flexibility than DSP for parallel processing and pipelined operations in order to process high resolution and high frame rate video processing. Vision-based gesture recognition technique is the best way to recognize the gesture. In gesture recognition, the image acquisition and image segmentation is there. In this paper, the image acquisition is shown and also the image segmentation techniques are discussed. In this, to capture the gesture the OV7670 CMOS camera chip sensor is used that is attached to FPGA DE-1 board. By using this gesture recognition, we can control any application in a non-tangible way.
• article_number: 8068593
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8068593
• html_url: https://ieeexplore.ieee.org/document/8068593/
• abstract_url: https://ieeexplore.ieee.org/document/8068593/
• publication_title: 2017 International Conference on Inventive Systems and Control (ICISC)
• conference_location: Coimbatore, India
• conference_dates: 19-20 Jan. 2017
• publication_number: 8062994
• is_number: 8068579
• publication_year: 2017
• publication_date: 19-20 Jan. 2017
• start_page: 1
• end_page: 4
• citing_paper_count: 5
• citing_patent_count: 0
• download_count: 711
• insert_date: 20171016
• index_terms:
  • ieee_terms:
    • Hidden Markov models
    • Gesture recognition
    • Field programmable gate arrays
    • Kalman filters
    • Cameras
    • Image color analysis
    • Image segmentation
  • author_terms:
    • FPGA
    • HMM
    • YCbCr
    • Kalman filter
  • dynamic_index_terms:
    • Gesture Recognition
    • Image Acquisition
    • Image Segmentation
    • Human-computer Interaction
    • User Interaction
    • Operator Of Order
    • Image Segmentation Techniques
    • Discrete-time
    • Linear System
    • Hidden Markov Model
    • Skin Color
    • Complexion
    • Skin Tone
    • Kalman Filter
    • True State
    • True Status
    • Truth Conditions
    • Use Of Gestures
    • Regeneration Buffer
    • Framebuffer
    • Display Memory
• isbn_formats:
  • format: Print on Demand(PoD) ISBN, value: 978-1-5090-4716-1, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-5090-4715-4, isbnType: New-2005
• authors:
  • Author Name: Deval Patel
    Affiliation: Charotar University of Science and Technology, Gujarat, India
    Author URL: https://ieeexplore.ieee.org/author/37086196428
    ID: 37086196428
    Order: 1
    Author Affiliations:
    • Charotar University of Science and Technology, Gujarat, India
    • G. H. Patel College of Engineering and Technology, Gujarat, India
  • Author Name: Rohit Parmar
    Affiliation: Charotar University of Science and Technology, Gujarat, India
    Author URL: https://ieeexplore.ieee.org/author/38467872300
    ID: 38467872300
    Order: 2
    Author Affiliations:
    • Charotar University of Science and Technology, Gujarat, India
    • G. H. Patel College of Engineering and Technology, Gujarat, India
  • Author Name: Arpan Desai
    Affiliation: Charotar University of Science and Technology, Gujarat, India
    Author URL: https://ieeexplore.ieee.org/author/37086197697
    ID: 37086197697
    Order: 3
    Author Affiliations:
    • Charotar University of Science and Technology, Gujarat, India
    • G. H. Patel College of Engineering and Technology, Gujarat, India
  • Author Name: Saurin Sheth
    Affiliation: Charotar University of Science and Technology, Gujarat, India
    Author URL: https://ieeexplore.ieee.org/author/37086194835
    ID: 37086194835
    Order: 4
    Author Affiliations:
    • Charotar University of Science and Technology, Gujarat, India
    • G. H. Patel College of Engineering and Technology, Gujarat, India

Image Sensor

• sensor_type: CMOS
• resolution: 640x480
• dynamic_range: unknown
• pixel_size: unknown
• dark_current: unknown

Optical Data

• focal_length: unknown
• aperture: unknown
• field_of_view: unknown
• distortion: unknown

Performance Metrics

• frame_rate: unknown
• signal_to_noise_ratio: unknown
• sensitivity: unknown
• shutter_speed: unknown
• power_consumption: unknown
• noise: unknown

Applications & Benefits

• cell_imaging: The CMOS image sensors are applicable in the context of capturing gestures in human-computer interaction, particularly through the OV7670 camera which is used for gesture recognition in this research.
• benefits: CMOS image sensors provide high resolution and real-time processing capabilities, which are beneficial in gesture recognition applications.

Supporting Organizations

• supported_by: G. H. Patel College of Engineering and Technology, Charotar University of Science and Technology

Manuscript Details

• publication_date: 19-20 Jan. 2017

Relevancy Score

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

Processed JSON Filename

request_2437a641-b3e9-4240-abb1-a7ca2b3e085a-gesture_recognition_using_fpga_and_ov7670_camera.json