3,786 research outputs found
Orientation covariant aggregation of local descriptors with embeddings
Image search systems based on local descriptors typically achieve orientation
invariance by aligning the patches on their dominant orientations. Albeit
successful, this choice introduces too much invariance because it does not
guarantee that the patches are rotated consistently. This paper introduces an
aggregation strategy of local descriptors that achieves this covariance
property by jointly encoding the angle in the aggregation stage in a continuous
manner. It is combined with an efficient monomial embedding to provide a
codebook-free method to aggregate local descriptors into a single vector
representation. Our strategy is also compatible and employed with several
popular encoding methods, in particular bag-of-words, VLAD and the Fisher
vector. Our geometric-aware aggregation strategy is effective for image search,
as shown by experiments performed on standard benchmarks for image and
particular object retrieval, namely Holidays and Oxford buildings.Comment: European Conference on Computer Vision (2014
Map online system using internet-based image catalogue
Digital maps carry along its geodata information such as coordinate that is important in one particular topographic and thematic map. These geodatas are meaningful especially in military field. Since the maps carry along this information, its makes the size of the images is too big. The bigger size, the bigger storage is required to allocate the image file. It also can cause longer loading time. These conditions make it did not suitable to be applied in image catalogue approach via internet environment. With compression techniques, the image size can be reduced and the quality of the image is still guaranteed without much changes. This report is paying attention to one of the image compression technique using wavelet technology. Wavelet technology is much batter than any other image compression technique nowadays. As a result, the compressed images applied to a system called Map Online that used Internet-based Image Catalogue approach. This system allowed user to buy map online. User also can download the maps that had been bought besides using the searching the map. Map searching is based on several meaningful keywords. As a result, this system is expected to be used by Jabatan Ukur dan Pemetaan Malaysia (JUPEM) in order to make the organization vision is implemented
Memory vectors for similarity search in high-dimensional spaces
We study an indexing architecture to store and search in a database of
high-dimensional vectors from the perspective of statistical signal processing
and decision theory. This architecture is composed of several memory units,
each of which summarizes a fraction of the database by a single representative
vector. The potential similarity of the query to one of the vectors stored in
the memory unit is gauged by a simple correlation with the memory unit's
representative vector. This representative optimizes the test of the following
hypothesis: the query is independent from any vector in the memory unit vs. the
query is a simple perturbation of one of the stored vectors.
Compared to exhaustive search, our approach finds the most similar database
vectors significantly faster without a noticeable reduction in search quality.
Interestingly, the reduction of complexity is provably better in
high-dimensional spaces. We empirically demonstrate its practical interest in a
large-scale image search scenario with off-the-shelf state-of-the-art
descriptors.Comment: Accepted to IEEE Transactions on Big Dat
Weighted universal image compression
We describe a general coding strategy leading to a family of universal image compression systems designed to give good performance in applications where the statistics of the source to be compressed are not available at design time or vary over time or space. The basic approach considered uses a two-stage structure in which the single source code of traditional image compression systems is replaced with a family of codes designed to cover a large class of possible sources. To illustrate this approach, we consider the optimal design and use of two-stage codes containing collections of vector quantizers (weighted universal vector quantization), bit allocations for JPEG-style coding (weighted universal bit allocation), and transform codes (weighted universal transform coding). Further, we demonstrate the benefits to be gained from the inclusion of perceptual distortion measures and optimal parsing. The strategy yields two-stage codes that significantly outperform their single-stage predecessors. On a sequence of medical images, weighted universal vector quantization outperforms entropy coded vector quantization by over 9 dB. On the same data sequence, weighted universal bit allocation outperforms a JPEG-style code by over 2.5 dB. On a collection of mixed test and image data, weighted universal transform coding outperforms a single, data-optimized transform code (which gives performance almost identical to that of JPEG) by over 6 dB
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