Cognitive Cameras: Assistive Vision Systems

被引:0
|
作者
Irick, Kevin M. [1 ]
Zientara, Peter A. [2 ]
Sampson, Jack [2 ]
Narayanan, Vijaykrishnan [2 ]
机构
[1] SiliconScapes LLC, State Coll, PA 16803 USA
[2] Penn State Univ, University Pk, PA USA
来源
2015 INTERNATIONAL CONFERENCE ON COMPILERS, ARCHITECTURE AND SYNTHESIS FOR EMBEDDED SYSTEMS (CASES) | 2015年
关键词
cognitive computing; vision; hardware acceleration; embedded system architecture; system-on-chip; wearable;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
As a benefactor of the proliferation of large scale integration, traditionally simple and unintelligent devices such as cameras have been transformed into key components of rich and engaging smart environments. By integrating machine perception algorithms, these cognitive cameras have the ability to perceive and understand their environments. A principal barrier to realizing the potential of cognitive cameras has been the absence of sufficient computing power within the device. This is especially true in wearable devices which are limited by both compute capability and energy. Hardware customization and specialization present effective solutions to the power and performance bottlenecks that have limited ubiquitous adoption. This work details the architecture, design, and evaluation of a cognitive camera system that employs custom hardware to meet both power and performance constraints. Furthermore we illustrate its use as an assistance system for the visually impaired.
引用
收藏
页码:188 / 188
页数:1
相关论文
共 50 条
  • [41] A framework for cognitive vision systems or identifying obstacles to integration
    Vincze, Markus
    Zillich, Michael
    Ponweiser, Wolfgang
    COGNITIVE VISION SYSTEMS: SAMPLING THE SPECTRUM OF APPROACHERS, 2006, 3948 : 279 - 293
  • [42] Face recognition by artificial vision systems:: A cognitive perspective
    Raducanu, Bogdan
    Vitria, Jordi
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2008, 22 (05) : 899 - 913
  • [43] On sampling the spectrum of approaches toward cognitive vision systems
    Nagel, H. -H.
    COGNITIVE VISION SYSTEMS: SAMPLING THE SPECTRUM OF APPROACHERS, 2006, 3948 : 315 - 319
  • [44] Investigation of data compression for digital video cameras in on-line machine vision systems
    Arshad, NM
    Harvey, DM
    Hobson, CA
    MACHINE VISION SYSTEMS FOR INSPECTION AND METROLOGY VII, 1998, 3521 : 325 - 333
  • [45] A Method for Measuring the Transfer Function of Digital Cameras Used in Biomedical Computer Vision Systems
    I. G. Palchikova
    E. S. Smirnov
    E. I. Solenov
    I. A. Iskakov
    Instruments and Experimental Techniques, 2022, 65 : 267 - 272
  • [46] ON-LINE DETECTION OF DEFECTS ON FRUIT BY MACHINE VISION SYSTEMS BASED ON THREE-COLOR-CAMERAS SYSTEMS
    Xu, Qiaobao
    Zou, Xiaobo
    Zhao, Jiewen
    COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE II, VOLUME 3, 2009, : 2231 - +
  • [47] Assistive Technology and Future Strategies for Vision Enhancement
    Dougherty, Bradley
    OPTOMETRY AND VISION SCIENCE, 2018, 95 (09) : 692 - 693
  • [48] Development of Color Vision Deficiency Assistive System
    Meng, Chong Kah
    Ismail, Fatimah Sham
    Ya'akup, Afiqamirul
    JURNAL TEKNOLOGI, 2015, 72 (02):
  • [49] Intelligent assistive exoskeleton with vision based interface
    Baklouti, Malek
    Monacelli, Eric
    Guitteny, Vincent
    Couvet, Serge
    SMART HOMES AND HEALTH TELEMATICS, 2008, 5120 : 123 - 135
  • [50] Barriers in utilisation of low vision assistive products
    Priya Sivakumar
    Rajesh Vedachalam
    Veena Kannusamy
    Annamalai Odayappan
    Rengaraj Venkatesh
    Pankaja Dhoble
    Fredrick Moutappa
    Shivananda Narayana
    Eye, 2020, 34 : 344 - 351