Saliency-driven dynamic configuration of HMAX for energy-efficient multi-object recognition

Sungho Park, Ahmed Al Maashri, Yang Xiao, Kevin M. Irick, Vijaykrishnan Narayanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


Object recognition is one of the most important tasks in computer vision due to its wide variety of applications from small hand-held devices to surveillance systems in large public facilities. Even though biologically inspired approaches have been recently revealed to take another significant step forward to reduce its large power consumption, it still consumes relatively large amounts of energy because of the immense amount of data and computations. Typically in such biologically inspired - often called neuromorphic - object recognition implementations, visual saliency feeds feature extraction to limit the amount of computations effectively by picking a pre-determined size of patches around salient locations of an image. In this work, we explore the design space of HMAX for neuromorphic feature-extraction and classification along with the trade-off between energy consumption and classification accuracy. In addition, a novel method to further reduce energy consumption is proposed by leveraging effort-level of HMAX according to the findings of visual saliency in an efficient manner. Experiments revealed that our dynamic configuration achieved 70.57% of energy reduction with only 1.05% of accuracy loss for accuracy-critical applications. For energy-critical applications, a proposed configurations trades off 5.07% accuracy to gain 91.72% reduction in energy consumption.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2013
PublisherIEEE Computer Society
Number of pages6
ISBN (Print)9781479913312
Publication statusPublished - 2013
Event2013 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2013 - Natal, Brazil
Duration: Aug 5 2013Aug 7 2013


Other2013 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2013


  • dynamic configuration
  • energy efficiency
  • FPGA
  • HMAX
  • object recognition
  • visual saliency

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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