[PDF] Top 20 Classification of Indian Classical Dance Steps using HOG Features
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Classification of Indian Classical Dance Steps using HOG Features
... Taguchi analysis calculates the Rank of each factor on basis of Delta value. In this experiment Bin Size is placed at Rank 1, followed by choice of classifier and cell size is at Rank 3. Therefore, it can be concluded ... See full document
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A Two-Staged Approach to Vision-Based Pedestrian Recognition Using Haar and Hog Features
... 3) Classification process: The classification stage receives regions of interest as input, ...pixels using the nearest-neighbor ...the features are extracted, transformed into a feature vector ... See full document
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Human Activity Recognition Using HOG Features
... detection using HOG features in which XML file of HOG features of positive and negative images of humans was generated and cascade classifier was ...phase, HOG feature vectors ... See full document
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High accuracy detection for T-cells and B-cells using deep convolutional neural networks
... two-layer classification scheme. At the first layer the HOG features based SVM classifier is used to detect cells and noise from ...the HOG features based SVM constitute the preselected ... See full document
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Video Annotation and Retrieval System using SIFT and HOG Features
... Gradients. HOG is a feature descriptor used to make the classification task easier under different conditions, main intension of feature descriptor is to generalize the object in such a way that the same ... See full document
5
Prediction of Lung Disease using HOG Features and Machine Learning Algorithms
... done using genetic algorithm and classification using Decision trees, K-nearest neighbor and ...images using the fuzzy c-means clustering and the texture features are extracted ... See full document
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Review of Techniques for Detecting Video Forgeries
... technique using HOG features and video compression properties we had the parameter cell size of the HOG feature generation set adaptively which increased the detection accuracy for spatial ... See full document
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Prediction of Fruits and Flowers using Image Analysis Techniques
... image. HOG features are obtained by orientation histograms of edge intensity in local ...The features such as gradient computation, orientation binning, descriptor blocks and block normalization are ... See full document
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A Survey on Vehicle Detection Techniques in Aerial Surveillance
... method using normalized color and edge map requires a large number of training samples and it is observed that the method using the SIFT and AF considerably reduces ...of HOG features for the ... See full document
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BENCHMARK EVALUATION OF HOG DESCRIPTORS AS FEATURES FOR CLASSIFICATION OF TRAFFIC SIGNS
... Traffic signs are usually installed on poles which are always vertical with respect to the ground level. However, for many reasons such as the nature of the ground or environmental effects, these traffic signs depart ... See full document
17
Segmentation of an Indian Classical Dance Videos using Different Segmentation Methods
... conversion features are retrieved to categorize the actions in an Indian classical dance video ...hence, features representing shapes and color can be used to interpret the dance ... See full document
5
Automatic Plant Detection Using HOG and LBP Features With SVM
... extract features and multiclass Support Vector Machine (SVM) is applied to classify the leaf ...of HOG+SVM with HOG feature extraction using cells size of 2 x 2, 4 x 4 and 8 x 8 are ...of ... See full document
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Dance-the-Music: an educational platform for the modeling, recognition and audiovisual monitoring of dance steps using spatiotemporal motion templates
... the Dance-the-Music, we have made the deliber- ate choice to implement a template-based approach to gesture modeling and ...from dance movements are organized into a fixed-size multidimensional feature ... See full document
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Towards enhanced arabic speech emotion recognition: comparison between three methodologies
... For classification, we adopted Supervised Learning approach, and implemented several classification algorithms: Support Vector Machines (SVM) with the Radial Basis Function (RBF) kernel, Neural Networks ... See full document
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One-Shot-Learning Gesture Recognition using HOG-HOF Features
... We used a simple [−1, 0, 1] gradient filter, applied in both directions and discretized the gradient orientations into 16 orientation bins between 0 ◦ and 180 ◦ . We had cells of size 40 × 40 pixels and blocks of size 80 ... See full document
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1. Image super resolution using sparse neighbor embedding and clustering algorithm
... direction. HOG features are calculated by taking orientation histograms of edge intensity in local ...Extract HOG features form each patch. We choose HOG rather than other low-level ... See full document
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Plant classification based on leaf Shape features using Neural Network
... To study the performance of the model first it is designed with the one hidden layer and five species row vector. This model takes input, as leaf shape features of samples of five species of the plants at ... See full document
5
Classifiers for Detection of Retinal DME Diseases in B-SCAN OCT Images using Image Processing Techniques
... images. Using both classifiers 45 OCT image data sets are used for training and after training for testing 40 images 10 normal and 30 DME affected OCT images are used for ...calculated using the Equations ... See full document
6
Gesture Recognition for Indian Sign Language using HOG and SVM
... of features obtain under complex background is efficiently used in Conditional Random Field (CRF) recognition system ...The features are extracted on the probability of segmentation and naming the data one ... See full document
5
Improving pedestrian detection using MPEG-7 descriptors
... In our second experiment, we applied the trained cascaded classifiers, described in Sect. 3, to a youtube video. For the evaluation we used a scenario of the driver‘s cab of a tram 1 . We manually annotated over 2,500 ... See full document
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