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automatic-video-summarization's Introduction

Acceleration of Video Summarization Algorithms with Graphics Processors (GPUs) and Multicore CPUs

This repository contains the code of my master degree dissertation created on 2014. It has the parallel and sequential implementations for automatic video summarization methods proposed in [1] and [2].

[1]Avila, S. E. F.; Lopes, A. P. B.; da Luz Jr., A. & de Albuquerque Araújo, A. (2011). Vsumm: A mechanism designed to produce static video summaries and a novel evaluation method. Pattern Recognition Letters, 32(1):56 - 68. Image Processing, Computer Vision and Pattern Recognition in Latin America.

[2]Cahuina, E. & Cámara Chávez, G. (2013). A new method for static video summarization using local descriptors and video temporal segmentation. At Graphics, Patterns and Images (SIBGRAPI), 2013 26th SIBGRAPI - Conference on, pp. 226-233.

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automatic-video-summarization's Issues

About feature_extraction.py about VSUMM

Hi!

I have three questions about your code(feature_extraction.py).

  1. I wondered why did you calculate hsv_histogram under 0.23 standard deviation? Although I read VSUMM paper, I was not able to find that thing. Rather, the paper showed "the standard deviation of monochromatic frames is equal to zero or a sufficiently small value close to zero".

  2. You calculated HSV histogram with [0,256] range but in the case of hue, the range is [0,180]. Is it not a problem to calculate HSV histogram?

  3. For histo_norm, you divided each value from a histogram by frams_size. Could you tell me about what's the meaning of frame_size and those contexts?

Thanks,

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