The History of Sloop

Timeline

Goals

PhD 2002--Image Retrieval.  Search for sustainability-related application of technology commences.  Lloyd Gamble introduces salamander problem.

ACCV 2004--Multiscale local features, marbled salamander.

  • Few clicks and fast matching.
  • Retrieval paradigm for Biometrics.
  • Medial axes and symmetry.

CVPR 2004 -- Affine invariant local features, marbled salamander.

  • May be too invariant, not selective enough.

JAE 2008 -- Multiscale PCA marbled salamander.

  • Impact in long-term study.
  • Randomized representations.

VAIB 08 -- Sloop v1.0 is released!

  • Relevance feedback.
  • Deformation Invariance.
  • Multiple preprocessing algorithms.

ICCV 09 -- Scale-Cascaded Alignment, MS-PCA, SIFT salamander, Sloop v2.0.

  • SCA, many applications.
  • Exemplar based specularity removal.
  • Randomized graphs and manifold distances.
  • Aggregation.

2010 -- Sloop Amop released. Also, Fowler's Toad and Tiger Salamander prototypes.

2011 -- Sloop Skinks

  • Citizen Science.
  • Crowd-sourcing relevance feedback.
  • Social media Sloop.
  • Assisted and automated modes. 

2012 -- Sloop v2.7 operational for conservation. First pattern retrieval engine in use.

MCPR 2013 -- Sloop v2.7 Gecko, Whale Shark

  • Hybrid contexts

MCPR 2014 -- Large-scale Relevance Feedback, Special Session on Animal Biometrics.

  1. Focus on Animal Biometrics for conservation of rare and endangered species.
  2. Several firsts:
    1. Application of generic visual features for Animal Biometrics.
    2. Animal Biometrics, a human-machine system, as a search engine.
    3. Animal biometrics by aggregated inference.
    4. Relevance feedback in animal biometrics.
    5. Large-scale relevance feedback by crowdsourcing.
  3. Other elements of approach
    1. Feedback symbiosis: matching to ease the citizen scientist's work, relevance feedback to improve algorithms. This is much different than simply using crowds to gather images.
    2. Interactive preprocessing for  segmentation, rectification and illumination.
    3. Novel methods.
      1. SCA.
      2. Exemplar-based specularity.
      3. Hybrid Context.
      4. Information-theoretic Relevance feedback.
      5. Information theoretic aggregation.
    4. Distributed system, short "idea to realization" cycle.
  4. Sloop consists of two servers: IPE (Image Processing Engine) and DEI (Data Exchange and Interaction). It sits on a Glassfish Server with Postgres bindings and makes use of DataNucleus/JPOX for DEI and uses Matlab/Octave for IPE.
    1. SloopLite is a desktop application for small collections.
    2. SloopMachine is a complete virtual machine.