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imisraimisra
committedJan 24, 2013
added sample data for aeroplanes and cows from Tomasz exemplars for VOC
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‎README.html

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</p>
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<div id="outline-container-1" class="outline-2">
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<h2 id="sec-1"><span class="section-number-2">1</span> Introduction</h2>
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<h2 id="sec-1"><span class="section-number-2">1</span> Tech Report</h2>
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<div class="outline-text-2" id="text-1">
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<p>
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<code>esvmTestCPP</code> is an implementation of the MATLAB Exemplar
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SVM<sup><a class="footref" name="fnr.1" href="#fn.1">1</a></sup> testing pipeline
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written in <code>C++</code>. Computationally intensive parts were written using
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ISPC <sup><a class="footref" name="fnr.2" href="#fn.2">2</a></sup> for SIMD performance.
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<p> The details and aim of this project can be found in our tech
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report. Please cite it if you use this code for any purpose. The
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code can be downloaded freely from our <a href="https://github.com/imisra/esvmTestCPP">github project page</a>.
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</p>
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<p>
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Ishan Misra, Abhinav Shrivastava, Martial Hebert - "<i>HOG and Spatial Convolution on SIMD Architecture</i>" CMU Tech Report XXXX (2013)
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</p>
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</div>
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</div>
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<div id="outline-container-2" class="outline-2">
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<h2 id="sec-2"><span class="section-number-2">2</span> Introduction</h2>
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<div class="outline-text-2" id="text-2">
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<p>
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If you use this code, please cite our tech-report <sup><a class="footref" name="fnr.3" href="#fn.3">3</a></sup>. The code
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can be downloaded freely from github <sup><a class="footref" name="fnr.4" href="#fn.4">4</a></sup>.
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<code>esvmTestCPP</code> is an implementation of the MATLAB <a href="https://github.com/abhi2610/exemplarsvm">Exemplar-SVM</a>
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testing pipeline written in <code>C++</code>. Computationally intensive parts
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were written using <a href="http://ispc.github.com/">ISPC</a> for SIMD performance.
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</p>
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<p>
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One may also use this code just for computing HOG features or
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</div>
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<h2 id="sec-2"><span class="section-number-2">2</span> Requirements</h2>
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<div class="outline-text-2" id="text-2">
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<div id="outline-container-3" class="outline-2">
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<h2 id="sec-3"><span class="section-number-2">3</span> Requirements</h2>
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<div class="outline-text-2" id="text-3">
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</div>
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<h2 id="sec-3"><span class="section-number-2">3</span> Setup</h2>
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<div id="outline-container-4" class="outline-2">
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<h2 id="sec-4"><span class="section-number-2">4</span> Setup</h2>
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<div class="outline-text-2" id="text-4">
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</div>
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<h2 id="sec-4"><span class="section-number-2">4</span> Directory structure</h2>
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<h2 id="sec-5"><span class="section-number-2">5</span> Directory structure</h2>
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</div>
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<h2 id="sec-5"><span class="section-number-2">5</span> Getting Started</h2>
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<div id="outline-container-6" class="outline-2">
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<h2 id="sec-6"><span class="section-number-2">6</span> Getting Started</h2>
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</div>
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<div id="outline-container-5-1" class="outline-3">
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<h3 id="sec-5-1"><span class="section-number-3">5.1</span> Input format for Exemplars</h3>
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<h3 id="sec-6-1"><span class="section-number-3">6.1</span> Input format for Exemplars</h3>
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<p> Suppose you have \(C\) classes, and for each class you have \(N_{i}\)
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(\(i=1\ldots C\)) exemplars. The input format as of this version is
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<h4 id="sec-5-1-1"><span class="section-number-4">5.1.1</span> Generating the exemplar data files</h4>
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<h4 id="sec-6-1-1"><span class="section-number-4">6.1.1</span> Generating the exemplar data files</h4>
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<p> The exemplar data is written in ASCII files. These files can be
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generated by using the <code>writeHogTxt</code> function in C++. It is also
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<h3 id="sec-5-2"><span class="section-number-3">5.2</span> Parameters</h3>
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<h3 id="sec-6-2"><span class="section-number-3">6.2</span> Parameters</h3>
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<p> The parameters for exemplar testing can be put together in the
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<code>struct esvmParameters</code>. A user can get default parameters by
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<h3 id="sec-5-3"><span class="section-number-3">5.3</span> Bounding box information</h3>
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<h3 id="sec-6-3"><span class="section-number-3">6.3</span> Bounding box information</h3>
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<p> The bounding boxes are stored in <code>struct esvmBoxes</code>. It internally
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stores them in a <code>float</code> array. It is recommended to use
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<h3 id="sec-5-4"><span class="section-number-3">5.4</span> Precision issues</h3>
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<h3 id="sec-6-4"><span class="section-number-3">6.4</span> Precision issues</h3>
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<p> Detection precision depends on which image resize function is
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used. As far as we can tell, it is best to use the same resize function
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<h3 id="sec-5-5"><span class="section-number-3">5.5</span> Performance characteristics</h3>
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<h3 id="sec-6-5"><span class="section-number-3">6.5</span> Performance characteristics</h3>
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<h2 id="sec-6"><span class="section-number-2">6</span> FAQs</h2>
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<h2 id="sec-7"><span class="section-number-2">7</span> FAQs</h2>
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<h3 id="sec-6-1"><span class="section-number-3">6.1</span> You keep mentioning <code>C++</code>, but all of your programming is <code>C</code> style!</h3>
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<h3 id="sec-7-1"><span class="section-number-3">7.1</span> You keep mentioning <code>C++</code>, but all of your programming is <code>C</code> style!</h3>
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<p> Correct. I mention <code>C++</code> because I did use a few <code>STL</code>
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libraries. There were a few headaches using <code>C++</code>
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<h3 id="sec-6-2"><span class="section-number-3">6.2</span> Can I use this for HOG computation only ?</h3>
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<h3 id="sec-7-2"><span class="section-number-3">7.2</span> Can I use this for HOG computation only ?</h3>
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<div class="outline-text-3" id="text-7-2">
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<p> Yes. Check out examples (<code>demo01</code>, <code>demo02</code>) in the <code>demo</code> directory.
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<h3 id="sec-6-3"><span class="section-number-3">6.3</span> Can I use this for Convolution computation only ?</h3>
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<h3 id="sec-7-3"><span class="section-number-3">7.3</span> Can I use this for Convolution computation only ?</h3>
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<h3 id="sec-7-4"><span class="section-number-3">7.4</span> What HOG feature do you compute ?</h3>
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<h3 id="sec-7-5"><span class="section-number-3">7.5</span> Is this library thread-safe ?</h3>
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<h3 id="sec-8-1"><span class="section-number-3">8.1</span> High priority</h3>
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<h2 class="footnotes">Footnotes: </h2>
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<p class="footnote"><sup><a class="footnum" name="fn.1" href="#fnr.1">1</a></sup> <a href="https://github.com/abhi2610/exemplarsvm">https://github.com/abhi2610/exemplarsvm</a>
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<p class="footnote"><sup><a class="footnum" name="fn.2" href="#fnr.2">2</a></sup> <a href="http://ispc.github.com/">http://ispc.github.com/</a>
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<p class="footnote"><sup><a class="footnum" name="fn.3" href="#fnr.3">3</a></sup> HOG and
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Spatial Convolution on SIMD Architecture - Ishan Misra, Abhinav
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Shrivastava, Martial Hebert. CMU Tech Report XXXX (2013)
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</p>
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<p class="footnote"><sup><a class="footnum" name="fn.4" href="#fnr.4">4</a></sup> <a href="https://github.com/imisra/esvmTestCPP">https://github.com/imisra/esvmTestCPP</a>
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‎README.org

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Version: 0.1 alpha^{2}
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Project Page: https://github.com/imisra/esvmTestCPP
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* Introduction
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* Tech Report
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The details and aim of this project can be found in our tech
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report. Please cite it if you use this code for any purpose. The
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code can be downloaded freely from our [[https://github.com/imisra/esvmTestCPP][github project page]].
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Ishan Misra, Abhinav Shrivastava, Martial Hebert - "/HOG and Spatial
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Convolution on SIMD Architecture/" CMU Tech Report XXXX (2013)
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=esvmTestCPP= is an implementation of the MATLAB Exemplar
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SVM[fn::https://github.com/abhi2610/exemplarsvm] testing pipeline
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written in =C++=. Computationally intensive parts were written using
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ISPC [fn::http://ispc.github.com/] for SIMD performance.
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* Introduction
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If you use this code, please cite our tech-report [fn::HOG and
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Spatial Convolution on SIMD Architecture - Ishan Misra, Abhinav
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Shrivastava, Martial Hebert. CMU Tech Report XXXX (2013)]. The code
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can be downloaded freely from github [fn::https://github.com/imisra/esvmTestCPP].
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=esvmTestCPP= is an implementation of the MATLAB [[https://github.com/abhi2610/exemplarsvm][Exemplar-SVM]]
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testing pipeline written in =C++=. Computationally intensive parts
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were written using [[http://ispc.github.com/][ISPC]] for SIMD performance.
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One may also use this code just for computing HOG features or
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performing spatial-convolution (without anything to do with Exemplar
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#tree -d
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##+end_src
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├── common: ISPC 64-bit Linux binary and internal files (Task system)
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* Getting Started
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** Input format for Exemplars
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"/Object detection with discriminatively trained part based models/",
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PAMI 2010
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It is different from the HOG popularized by the "Pedestrian detection"
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It is different from the HOG popularized by the "Pedestrian detection"
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application from Navneet Dalal's paper (N. Dalal and B. Triggs,
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"/Histograms of oriented gradients for human detection/", CVPR
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2005).
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This latest reincarnation of the HOG feature is generally considered
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detection tasks.
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This latest reincarnation of the HOG feature is generally
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considered to be more discriminative than the earlier versions,
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for object detection tasks.
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** Is this library thread-safe ?
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Unfortunately, no. The reason has to do with the ISPC task
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=read/write= functions in MATLAB and C++. No changes expected in the
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** Low priority
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- Fix dependency issues on GCC and Linux.
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- 32 bit binary for ISPC ?
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- =paramters->flipImage= to be implemented.
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- Fix dependency issues on GCC and Linux. The =__expect= macros, and
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=memalign= calls need to be changed.
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- Include a 32 bit binary for ISPC ?
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- =parameters->flipImage= to be implemented.

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