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This paper presents a study on hand gesture distinguish ability between Speeded Up Robust Features(SURF) and Scale Invariant Feature Transform(SIFT) feature descriptors of hand images. Then bag of visual words are to map these descriptors to a dimension vector and support vector machine(SVM) classifer is trained to recognize hand gesture. Experimental results demonstrate that SURF feature descriptors...
In this paper, we present a classification method based on the multi-level brain partitions. Bag-of-visual-words model is used. Firstly, the representative SIFT features are extracted from brain template as the basic visual words. Secondly, individual MR images are described using the basic visual words and support vector machine classifiers are trained for different brain partitions respectively...
To improve the performance of multi-object tracking in the complex scenario with frequent occlusions and cluttered backgrounds, a novel online multi-object tracking algorithm based on fuzzy logic is proposed. In the proposed algorithm, firstly, the similarity measure of multiple features between the objects and the measurements are calculated, including the background-weighted color feature, histogram...
Gastroenterology imaging is a diagnostic procedure that incorporates various computer vision challenges for the design of assisted diagnostic systems. The most typical challenge is the design of more adequate visual descriptors that can assist the classification algorithms in getting good diagnostic results. Literature shows that most of the texture descriptors for feature extraction from gastric...
Encoding of reward valence has been shown in various brain regions, including deep structures such as the substantia nigra as well as cortical structures such as the orbitofrontal cortex. While the correlation between these signals and reward valence have been shown in aggregated data comprised of many trials, little work has been done investigating the feasibility of decoding reward valence on a...
In this paper, we propose a new local descriptor for action recognition in depth images. Our proposed descriptor jointly encodes the shape and motion cues using surface normals in 4D space of depth, time, spatial coordinates and higher-order partial derivatives of depth values along spatial coordinates. In a traditional Bag-of-words (BoW) approach, local descriptors extracted from a depth sequence...
The purpose of this study is to create a software system to facilitate the organization of and searching for social images acquired from social sites on the Web (such as Facebook or Flikr), taking into account the images' features as well as user preferences. To achieve our goal, we design a solution based on image clustering, grouping together images sharing similar semantic and visual features,...
The images, captured by camera, might suffer from poor contrast, saturation artefacts or improper brightness. Hence, image enhancement becomes an important step to improve the quality of image. Images are enhanced such that there is change in intensity or saturation component, keeping hue unchanged. Often, gamut problem arises when transforming from one plane to another. In this paper, the technique...
Cartoons are an informative way for creating awareness; children take keen interest in watching cartoons and spend leisure time in front of television. Unfortunately there is an inclination towards violence and other objectionable scenes in cartoon videos that have very bad impact on the developing personality of children. Extensive use of such violent scenes is one of the factors of increase of violence...
In the past few years, image retrieval has been one of the hot spots in computer vision field. Among many image retrieval techniques, Bag-of, Word (BoW) model is one of the effective and efficient methods that can search images with visual vocabularies and it is insensitive to massive data and various geometric attacks. But the classical BoW algorithm used some descriptors as its visual words, such...
Humans have the capability to quickly prioritize external visual stimuli and localize their most interest in a scene. Inspired by this mechanism, we propose a robust object tracking algorithm based on visual attention. We fuse motion feature and color feature to estimate the target state under the guidance of saliency map. Principal Component Analysis method is used to compute saliency feature based...
We address the problem of modeling complex target behavior using a stochastic model that integrates object dynamics, statistics gathered from the environment and semantic knowledge about the scene. The method exploits prior knowledge to build point-wise polar histograms that provide the ability to forecast target motion to the most likely paths. Physical constraints are included in the model through...
The region of interests (ROI) detection plays an important role in the remote sensing data processing and analysis. In this paper, a new region of interest detection method based on salient feature clustering for remote sensing images is proposed. Four steps are included in the proposed method. First, the information salient feature maps are constructed by computing the spectrum information and histograms...
This paper addresses the problem of aggregating local binary descriptors for large scale image retrieval in mobile scenarios. Binary descriptors are becoming increasingly popular, especially in mobile applications, as they deliver high matching speed, have a small memory footprint and are fast to extract. However, little research has been done on how to efficiently aggregate binary descriptors. Direct...
Due to the ever increasing commercial availability of High Dynamic Range (HDR) content and displays, backward compatibility of HDR content with Standard Dynamic Range displays is currently a topic of high importance. Over the years, a significant amount of Tone Mapping Operators (TMOs) have been proposed to adapt HDR content to the restricted capabilities of SDR displays. Among them, the Histogram...
Breeding cows are known to engage in sociality, in which they interact and form groups. This paper proposes a method of detecting the interaction between breeding cows from time-series pictures of pastures by a similar image retrieval method using a Bag of Visual Words. We divided the interaction detection into three tasks: detecting a pair of cows in an interaction, pinpointing the time and the place...
This paper presents several pictorial and graphical techniques that may be used for effectively visualizing type-2 fuzzy membership functions (T2 FMFs). In our first proposed technique, two-dimensional data sets have been modeled using grayscale entropies to make the uncertainty interpretation easier. Next, the concept of a vertical drill and a primary membership drill has been introduced to obtain...
In this paper, we propose combined visual features for person re-identification. Our features are based on the multiple hand-crafted visual features. The proposed features are a combination of histogram from the RGB, YUV and HSV color channels, LBP and SIFT features. Then we use different distance metric learning methods to measure the similarity of the same persons and different persons. Experimental...
When analyzing news videos, finding an efficient way of extracting visual memes is very important. Videos might be very long and visual meme extraction itself is computationally expensive, so it is essential to make this process as efficient as possible. A way to do this is to eliminate as many key frames as possible even before extracting the visual memes. Since anchor person frames contribute little...
Tone mapping can compress the color range of HDR (high dynamic range) image to produce its LDR (low dynamic range) image. However, without preserving the original scene detail, tone mapping may produce various artifacts and their fidelity will be severely decreased. In this paper, we propose a new detail-preserving refinement method to efficiently improve the fidelity of tone mapping. Its overall...
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