Resource-aware harris corner detection based on adaptive pruning

Johny Paul, Walter Stechele, Manfred Kröhnert, Tamim Asfour, Benjamin Oechslein, Christoph Erhardt, Jens Schedel, Daniel Lohmann, Wolfgang Schröder-Preikschat

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations


Corner-detection techniques are being widely used in computer vision - for example in object recognition to find suitable candidate points for feature registration and matching. Most computer-vision applications have to operate on real-time video sequences, hence maintaining a consistent throughput and high accuracy are important constrains that ensure high-quality object recognition. A high throughput can be achieved by exploiting the inherent parallelism within the algorithm on massively parallel architectures like many-core processors. However, accelerating such algorithms on many-core CPUs offers several challenges as the achieved speedup depends on the instantaneous load on the processing elements. In this work, we present a new resource-aware Harris corner-detection algorithm for many-core processors. The novel algorithm can adapt itself to the dynamically varying load on a many-core processor to process the frame within a predefined time interval. The results show a 19% improvement in throughput and an 18% improvement in accuracy.

Original languageEnglish
Title of host publicationArchitecture of Computing Systems, ARCS 2014 - 27th International Conference, Proceedings
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319048901
StatePublished - 2014
Event27th International Conference on Architecture of Computing Systems, ARCS 2014 - Luebeck, Germany
Duration: 25 Feb 201428 Feb 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8350 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference27th International Conference on Architecture of Computing Systems, ARCS 2014


  • Harris corner detection
  • adaptive pruning
  • invasive computing
  • resource-aware programming


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