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  • PROJECTS ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΕΙΚΟΝΑΣ/VIDEO Σπύρος Φωτόπουλος 1

    Aggregating local descriptors into a compact image

    representation -VLAD descriptor

    Images and corresponding VLAD descriptors, for K=16 centroids. The components of the descriptor are represented like SIFT, with negative

    components in red.

    Σχετικό υλικό: Paper-Aggregating local descriptors into a compact image representation

    Jegou, H. ; INRIA Rennes, Rennes, France ; Douze, M. ; Schmid, C. ; Perez, P. http://lear.inrialpes.fr/pubs/2010/JDSP10/jegou_compactimagerepresentation.pdf

    https://hal.inria.fr/inria-00633013/PDF/jegou_aggregate.pdf

    Πρόκειται για μία απλή διαδικασία εξαγωγής χαρακτηριστικού σε εικόνα που βασίζεται στην

    ομαδοποίηση k-means. Είναι ο γνωστός αλγόριθμος VLAD

    Ζητείται η υλοποίηση του και η εφαρμογή σε «απόσταση» εικόνων – ανάκτηση εικόνων

    http://ieeexplore.ieee.org/search/searchresult.jsp?searchWithin=%22Authors%22:.QT.Jegou,%20H..QT.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchWithin=%22Authors%22:.QT.Douze,%20M..QT.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchWithin=%22Authors%22:.QT.Schmid,%20C..QT.&newsearch=true http://ieeexplore.ieee.org/search/searchresult.jsp?searchWithin=%22Authors%22:.QT.Perez,%20P..QT.&newsearch=true http://lear.inrialpes.fr/pubs/2010/JDSP10/jegou_compactimagerepresentation.pdf https://hal.inria.fr/inria-00633013/PDF/jegou_aggregate.pdf

  • PROJECTS ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΕΙΚΟΝΑΣ/VIDEO Σπύρος Φωτόπουλος 2

    Efficiently Searching for Similar Images

    Σχετικό paper:

    http://cacm.acm.org/magazines/2010/6/92473-efficiently-searching-for-similar-

    images/fulltext

    Ζητείται η κατασκευή ιστογράμματος -The Pyramid Match Algorithm -όπως περιγράφεται

    στο σχετικό paper(&2.2) και η εφαρμογή του σε “απόσταση- ομοιότητα” εικόνων.

    http://cacm.acm.org/magazines/2010/6/92473-efficiently-searching-for-similar-images/fulltext http://cacm.acm.org/magazines/2010/6/92473-efficiently-searching-for-similar-images/fulltext

  • PROJECTS ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΕΙΚΟΝΑΣ/VIDEO Σπύρος Φωτόπουλος 3

    Depth Maps for Object Recognition

    Summary As depth data is increasingly common in vision systems through the widespread

    availability of RGB-D cameras, deriving useful information from that data is

    becoming more important. Recently, there exist large datasets of RGB-D data

    as well as algorithms that create features from depth data ([1, 2]). I would

    like to further explore the usefulness of depth images by experimenting with

    the important phase in the vision , defining features.

    Technical Details

     RGB-D dataset provided by [1] should be used http://rgbd-dataset.cs.washington.edu/dataset.html

    http://rgbd-dataset.cs.washington.edu/index.html

     Create a recognition system (HOG features with SVM classifier)

     You can use any type of classifier

    References [1] K. Lai, L. Bo, X. Ren, and D. Fox. "A Large-Scale Hierarchical Multi-View

    RGB-D Object Dataset". IEEE International Conference on on Robotics

    and Automation, 2011

    [2] L. Bo, K. Lai, Xiaofeng Ren, and D. Fox "Object Recognition with Hierar-

    chical Kernel Descriptors"

    [3] Martin Koppel, Mehdi Ben Makhloufz, and Patrick Ndjiki-Nya "Optimized

    Adaptive Depth Map Filtering"

    [4] Young-Woo Kim, Karam Kim, and Jong-Il Park "Refinement of Depth Map

    by Combining Course Depth and Surface Normal"

    http://rgbd-dataset.cs.washington.edu/dataset.html http://rgbd-dataset.cs.washington.edu/index.html

  • PROJECTS ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΕΙΚΟΝΑΣ/VIDEO Σπύρος Φωτόπουλος 4

    Κατάτμηση εικόνας με διαδικασία «Laplacian Eigenmaps»

    σχετικά papers:

    I. Tziakos, C. Theoharatos, N. Laskaris, and G. Economou, "Color image segmentation using

    Laplacian eigenmaps," Journal of Electronic Imaging, vol. 18, iss. 2, 2009

    IoannisTziakos, Nikolaos Laskaris and Spiros Fotopoulos, "Multivariate Image Segmentation

    using Laplacian Eigenmaps", In Proc. of European Signal Processing Conference (EUSIPCO),

    Sept. 2004, Vienna, Austria, pp 945-948

     Ζητείται η υλοποίηση του Αλγορίθμου όπως περιγράφεται στα παραπάνω Papers

     Και εφαρμογή σε RGB εικόνα (input)

  • PROJECTS ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΕΙΚΟΝΑΣ/VIDEO Σπύρος Φωτόπουλος 5

    Create Pointillism Art with 3 Primary Colors from Natural Images

    Description Pointillism is a branch of impressionism that can be dated back to the late 19th century. It is a painting

    technique that only uses tiny, distinct dots to form patterns of color. It enjoys a duality in being both

    discrete up close (the dots) and continuous from distance (the patterns). Combining this artistic

    inspiration with the techniques of digital image processing, we want to develop a special image filter

    that creates pointillism art from ordinary digital images.

    Plan

    The process of creating pointillism art will be as followed:

    (1) We take an image.

    (2) We will apply various image processing techniques to our image, such as blurring the image with a

    structuring element that is larger and proportional to the size of the dots we want to use in our

    pointillism art.

    (3) We will then downsample the image to reduce the resolution of the image. By blurring the image and

    downsampling, we want to create an image that allows us to more easily

    deconstruct the image into Pointillism art composed of 3 primary colors.

    (4) After the preprocessing, we will determine the intensity map of the image by converting it to

    grayscale. The intensity map of the image will be used to determine a density map of the dots in our

    subsequent pointillism art.

    (5) We will apply histogram normalization to the image to make it more saturated so that the

    distribution of colors in the image can be better mapped to the limited gamut of colors we can create

    with three primary colors. Then we can create a linear mapping between the colors in the image to the

    colors we want to use for the dots.

    (6) Once the conversion is done, we will analyze pixels in the original image to create regions of dots

    that represent each pixel of the original image. We will determine the distribution of dots and color in the

    regions to closely represent the original pixel in an artistic manner. We will overlap the resulting regions

    of dots, to reduce artifacts and create a more blended distribution of dots across the entire resulting

    pointillism image.

    (7) Once our Pointillism art is created, we will display the image on a printout. The goal is if you stand

    close to the art, the art looks like a bunch of dots, but the farther you stand from it, then it looks like an

    artistic representation of the image.

    The procedures here are tentative and subject to changes for the pursuit of aesthetics.

    References

    Dongxiang Chi, “A Natural Image Pointillism with Controlled Ellipse Dots,” Advances in Multimedia, vol. 2014,

    Article ID 567846, 16 pages, 2014. doi:10.1155/2014/567846

    Greenberg, Ira, Dianna Xu, and Deepak Kumar. "Image SpecialFX: Pointilism." Processing Creative Coding and

    Generative Art in Processing 2. Dordrecht: Springer, 2013. 399-401. Print.

    Lansdown, John, and Simon Schofield. "Expressive Rendering: A Review of Nonphotorealistic Techniques."

    Computer Graphics and Applications, IEEE 15.3 (1995): 29-37. IEEE. Web. 3 Nov. 2015.

    Luong, Tran-Quan, Ankush Seth, Allison Klein, and Jason Lawrence. "Isoluminant Color Picking for Non-

    Photorealistic Rendering."SpringerReference (2011): n. pag. Isoluminant Color Picking for Non-Photorealistic

    Rendering. Princeton, 2005. Web. 3 Nov. 2015.

    .

    Λεπτομέρειες για το project στο παρακάτω paper:

    http://web.stanford.edu/class/ee368/Project_Autumn_1516/Reports/Hong_Liu.pdf

     Ζητείται να γίνει ο σχετικός κώδικας

    http://www.cs.virginia.edu/~jdl/papers/isolum/luong_gi05.pdf http://www.cs.virginia.edu/~jdl/papers/isolum/luong_gi05.pdf http://web.stanford.edu/class/ee368/Project_Autumn_1516/Reports/Hong_Liu.pdf

  • PROJECTS ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΕΙΚΟΝΑΣ/VIDEO Σπύρος Φωτόπουλος 6

  • PROJECTS ΨΗΦΙΑΚΗ ΕΠΕΞΕΡΓΑΣΙΑ ΕΙΚΟΝΑΣ/VIDEO Σπύρος Φωτόπουλος 7

    Mobile Haze Removal

    Motivation In the last couple decades, China has developed its economy by largely expanding heavily polluting

    industries. Public concern over the environmental consequ