A Novel Method For Low Power Hand Gesture Recognition In Smart Consumer Applications

• doi: 10.1109/ICCTICT.2016.7514602
• title: A novel method for low power hand gesture recognition in smart consumer applications
• publisher: IEEE
• isbn: 978-1-5090-0083-8
• issn:
• rank: 1222
• access_type: LOCKED
• content_type: Conferences
• abstract: The latest developments in CMOS sensor technology and vision algorithms have enabled the imaging systems to penetrate in newer and complex applications such as object detection and human machine interface (HMI). In some of these applications, the imaging and vision subsystem may be used to continuously monitor the environment and detect the object of interest (e.g. hand) which necessitates this sub-system to be always switched on. This sub-system uses complex object detection algorithms which are computationally expensive and consume lot of power. The power consumption along with performance is the key deterrents for the industrialization of such applications. Even though, performance improvement is quite active research area, it's not so much the case for low power implementation. In this paper, we address this issue from system point of view and propose a method to reduce the power consumption in hand gesture recognition systems. The proposed method of frame rate adaptation results in significant power saving and can be used for industrialization of such applications.
• article_number: 7514602
• pdf_url: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7514602
• html_url: https://ieeexplore.ieee.org/document/7514602/
• abstract_url: https://ieeexplore.ieee.org/document/7514602/
• publication_title: 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT)
• conference_location: New Delhi, India
• conference_dates: 11-13 March 2016
• publication_number: 7505515
• is_number: 7514538
• publication_year: 2016
• publication_date: 11-13 March 2016
• start_page: 326
• end_page: 330
• citing_paper_count: 1
• citing_patent_count: 0
• download_count: 227
• insert_date: 20160718
• index_terms:
  • ieee_terms:
    • Gesture recognition
    • Feature extraction
    • Power demand
    • Skin
    • Video sequences
    • Imaging
    • Switches
  • author_terms:
    • CMOS Sensor
    • ISP
    • Object Detection
    • HMI
    • Gesture Recognition
    • Low Power
  • dynamic_index_terms:
    • Hand Gestures
    • Gesture Recognition
    • Hand Gesture Recognition
    • Power Consumption
    • Object Detection
    • Frame Rate
    • False Negative
    • Image Processing
    • Field Of View
    • Image Features
    • Imaging Characteristics
    • Color Space
    • Color Components
    • Image Sensor
    • Camera Sensor
    • Preparation Phase
    • Video Sequences
    • Usage Intention
    • Average Frame
    • Average Frame Rate
    • Image Processing Tasks
    • Standby Mode
    • Gesture Classification
• isbn_formats:
  • format: Print on Demand(PoD) ISBN, value: 978-1-5090-0083-8, isbnType: New-2005
  • format: Electronic ISBN, value: 978-1-5090-0082-1, isbnType: New-2005
• authors:
  • Author Name: Mahesh Chandra
    Affiliation: Consumer Products Division, STMicroelectronics Pvt. Ltd., Greater Noida, Uttar Pradesh, India
    Author URL: https://ieeexplore.ieee.org/author/37085772259
    ID: 37085772259
    Order: 1
    Author Affiliations:
    • Consumer Products Division, STMicroelectronics Pvt. Ltd., Greater Noida, Uttar Pradesh, India
  • Author Name: Brejesh Lall
    Affiliation: Electrical Engineering Department, Indian Institute of Technology, Delhi, India
    Author URL: https://ieeexplore.ieee.org/author/37402514000
    ID: 37402514000
    Order: 2
    Author Affiliations:
    • Electrical Engineering Department, Indian Institute of Technology, Delhi, India

Image Sensor

• sensor_type: CMOS
• resolution: Not specified
• dynamic_range: Not specified
• pixel_size: Not specified
• dark_current: Not specified

Optical Data

• focal_length: Not specified
• aperture: Not specified
• field_of_view: Not specified
• distortion: Not specified

Performance Metrics

Applications & Benefits

• cell_imaging: Not specified
• benefits: Not specified

Supporting Organizations

• supported_by: Not specified

Manuscript Details

• publication_date: 11-13 March 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
  • cell_imaging
  • benefits
  • supported_by

Processed JSON Filename

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