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Occlusion-Robust Cattle Pose Estimation for Precision Livestock Monitoring Using Hierarchical Locality Refinement. [PDF]

Animals (Basel)
Wang Y, Li N, He D, Sun S, Chu X, Qin Z, Xue F, Yi J, Wu H, Zhang HS, Zhao F.   +10 more
europepmc   +1 more source

Hardware Friendly Robust Synthetic Basis Feature Descriptor

Electronics (Switzerland), 2019
Finding corresponding image features between two images is often the first step for many computer vision algorithms. This paper introduces an improved synthetic basis feature descriptor algorithm that describes and compares image features in an efficient
Alok Desai, Meng Yu, Dong Zhang
exaly   +2 more sources

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Harris feature vector descriptor

2010 International Conference on Machine Learning and Cybernetics, 2010
This paper defines a new image feature called Harris feature vector, which is able to describe the image gradient distribution in an effective way. By computing the mean and the standard deviation of the Harris feature vector in a local image region, novel descriptors are constructed for feature matching which are invariable to image rigid ...
Xu-Guang Wang, Jie Su, Hai-Yan Cheng
openaire   +2 more sources

Optimization and Implementation of Synthetic Basis Feature Descriptor on FPGA

Electronics (Switzerland), 2020
Feature detection, description, and matching are crucial steps for many computer vision algorithms. These steps rely on feature descriptors to match image features across sets of images.
Dah-Jye Lee
exaly   +2 more sources

MULTITASK FEATURE SELECTION WITH TASK DESCRIPTORS

Biocomputing 2016, 2015
Machine learning applications in precision medicine are severely limited by the scarcity of data to learn from. Indeed, training data often contains many more features than samples. To alleviate the resulting statistical issues, the multitask learning framework proposes to learn different but related tasks jointly, rather than independently, by sharing
Victor Bellon, Véronique Stoven, Chloé-Agathe Azencott   +2 more
openaire   +3 more sources

The Descriptiveness of Feature Descriptors with Reduced Dimensionality

2021
Nowadays, depth data has an important role in many applications. The sensors which can capture depth data became essential parts of autonomous vehicles. These sensors record a huge amount of 3D data (point clouds with x, y, and z coordinates). Furthermore, for many point cloud processing applications, it is important to calculate feature vectors that ...
Dániel Varga, János Márk Szalai-Gindl, Sándor Laki   +2 more
openaire   +2 more sources

Matching Affine Features with the SYBA Feature Descriptor

2014
Many vision-based applications require a robust feature descriptor that works well with image deformations such as compression, illumination, and blurring. It remains a challenge for a feature descriptor to work well with image deformation caused by viewpoint change.
Alok Desai, Dah-Jye Lee, Dan Ventura
openaire   +1 more source

A Hybrid Image Feature Descriptor for Classification

2015 11th International Conference on Computational Intelligence and Security (CIS), 2015
Feature extraction methods have an important role in image classification. In this paper, a hybrid texture feature descriptor is proposed by utilizing the attributes of two complementary features, PRICoLBP and LPQ. PRICoLBP performs well in the case of geometric and photometric variations however it does not properly express the local texture of an ...
Hassan Dawood, Hussain Dawood, Ping Guo 0002   +2 more
openaire   +2 more sources

Evaluation of feature descriptors for texture classification

Journal of Electronic Imaging, 2012
Successful execution of tasks such as image classification, object detection and recognition, and scene classification depends on the definition of a set of features able to describe images effectively. Texture is among the features used by the human visual system.
William Robson Schwartz, Fernando Roberti de Siqueira, Hélio Pedrini   +2 more
openaire   +2 more sources

Feature detectors and descriptors for fisher vectors

2015 IEEE 5th International Conference on Consumer Electronics - Berlin (ICCE-Berlin), 2015
Visual search and classification applications often use local features for image representation and description. Various detectors and descriptors have been developed for extracting these features. The local descriptors can be aggregated into a global image signature for a more compact representation.
Iris Heisterklaus, Philipp Gräbel
openaire   +2 more sources