HOG features
Human Activity Recognition Using HOG Features
... of HOG descriptors and used SVM for human ...proposed HOG descriptor which was constructed by converting the tracking region to the grids of Histograms of Oriented Gradient (HOG) descriptor, and then ...
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A Two-Staged Approach to Vision-Based Pedestrian Recognition Using Haar and Hog Features
... Haar features. The second stage classifies the incoming samples using HOG-based features and a linear ...Haar features can be calculated rapidly and do not need high-detailed input for ...
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An Automatic Annotation Algorithm for Deep Learning Image Datasets Based on HOG Features
... Abstract. Labeled data is crucial for deep learning model training, but it is mainly based on manual annotation. This paper proposes an automatic annotation algorithm for deep learning image datasets based on HOG ...
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Prediction of Lung Disease using HOG Features and Machine Learning Algorithms
... Copyright to IJIRCCE DOI: 10.15680/IJIRCCE.2016. 0401013 67 small connected regions called cells, and also for the pixels within each cell, a histogram of gradient orientations is compiled. The descriptor is then the ...
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Video Annotation and Retrieval System using SIFT and HOG Features
... on HOG and SIFT features for training the SVM classifiers is ...on HOG features are best as compared to SIFT ...of HOG and SIFT feature extraction the annotation files are created, the ...
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Classification of Indian Classical Dance Steps using HOG Features
... based features were used [4]. Apiraksa et.al worked on simple poses. Features were extracted based on compactness and radial ...this HOG, Zernike moments (ZM), Scale Invariants Feature Transform ...
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Human Action Recognition Using SURF and HOG Features from Video Sequences
... Typically, the codebook is generated using the k-means algorithm. After generating the visual vocabulary i.e. the codebook, every video can be represented by the bag-of-features model. The bag-of-features ...
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Facial Expression Recognition using Fusion of LBP and HoG Features
... Face is split into 3 parts which are Eyes, Left and Right Cheek that includes Nose, Mouth. The aim of this action is to get feature of face locally. In expression recognition problem, part of faces like eyes, mouth, nose ...
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Efficient Handwritten Digit Classification using User-defined Classification Algorithm
... compute the HOG features. This approach got 99.36% when applied on MNIST database. But while applying on other databases it is decreased to 97.13. Jisha proposed Convolution Neural Networks (CNNs) consist ...
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Classifiers for Detection of Retinal DME Diseases in B-SCAN OCT Images using Image Processing Techniques
... the HOG features from the retinal OCT images the feature vectors are fed into the SVMs and Naïve Bayes classifiers and the steps involved are shown in Figure ...
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A pillar-based microfluidic chip for T-cells and B-cells isolation and detection with machine learning algorithm
... distribution features was proposed to distinguish T-cells and B-cells fast and ...robustly. HOG features were utilized to detect cells from background and noise; color distribution features ...
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Ontology Based Video Annotation and Retrieval System
... and HoG features For recognition of objects present in the video we need to train different classifiers for object ...this features from the images that are invariant to image formation process and ...
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Review of Techniques for Detecting Video Forgeries
... the HOG features are generated for each block and simultaneously find matches for individual block ...the HOG features are generated ...
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Modified HOG Descriptor-Based Banknote Recognition System
... In this research, we implemented a procedure for enhancing and cleaning up banknote images. It involves converting to grayscale then employing Gamma Correction and Histogram equalization to improve the image luminance ...
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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 ...
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Brahmi word recognition by supervised techniques
... loop features) and introduced some sets of rules to recognise Malayalam ...code features, and HOG for feature extraction and compared the performance of all feature extraction methods, with ANN as ...
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Automatic facial expression recognition based on MRELBP and compressive sensing
... and HOG features. MRELBP & HOG can efficiently extract the textures, and they are a natural choice for feature extraction because of its several ...and HOG feature space which helps to ...
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A Face Detection Method Based on Sliding Window and Support Vector Machine
... The contribution of this paper is to design a face detection method based on support vector machine with a mechanism of the sliding window. This method firstly divides the image into blocks, then extracts the HOG ...
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Improving pedestrian detection using MPEG-7 descriptors
... (HOG) features, since they yield good results in the field of pedestrian detec- tion, but fail completely in some ...additional features like Haar Wavelets (Pa- pageorgiou et ...combines HOG ...
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Research on Intelligent Vehicle Pedestrian Detection Technology
... the HOG+SVM pedestrian detection method proposed by previous researchers is ...improved. HOG+SVM detects the pedestrian's speed is relatively slow, and the detection accuracy is not very ...for HOG ...
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