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Subject = Feature extraction;
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Displaying Results 1 - 25 of 29 on page 1 of 2
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A combined audio-visual contribution to event detection in field sports broadcast video. Case study: Gaelic football
(2003)
Sadlier, David A.; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
A combined audio-visual contribution to event detection in field sports broadcast video. Case study: Gaelic football
(2003)
Sadlier, David A.; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
Abstract:
In this paper we propose novel, audio-visual analysis techniques for event detection in broadcast TV sports video content. The scope of the design is constrained to the specialized domain of 'field sport', and specifically, Gaelic Football is presented as an experimental case study. We show that a combination of speech-band energy tracking in the audio domain, coupled with colour dominance pattern recognition in the video domain, provides a useful contribution to event detection for broadcast Gaelic Football matches. It is projected that, any conclusions made therein may be extended such that they function on sports content of a similar nature such as American Football, Australian Rules, Rugby Union etc.
http://doras.dcu.ie/244/
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A fully automatic CAD-CTC system based on curvature analysis for standard and low-dose CT data
(2008)
Chowdhury, Tarik A.; Whelan, Paul F.; Ghita, Ovidiu
A fully automatic CAD-CTC system based on curvature analysis for standard and low-dose CT data
(2008)
Chowdhury, Tarik A.; Whelan, Paul F.; Ghita, Ovidiu
Abstract:
Computed tomography colonography (CTC) is a rapidly evolving noninvasive medical investigation that is viewed by radiologists as a potential screening technique for the detection of colorectal polyps. Due to the technical advances in CT system design, the volume of data required to be processed by radiologists has increased significantly, and as a consequence the manual analysis of this information has become an increasingly time consuming process whose results can be affected by inter- and intrauser variability. The aim of this paper is to detail the implementation of a fully integrated CAD-CTC system that is able to robustly identify the clinically significant polyps in the CT data. The CAD-CTC system described in this paper is a multistage implementation whose main system components are: 1) automatic colon segmentation; 2) candidate surface extraction; 3) feature extraction; and 4) classification. Our CAD-CTC system performs at 100% sensitivity for polyps larger than 10 mm, 92% s...
http://doras.dcu.ie/2453/
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A generic news story segmentation system and its evaluation
(2004)
O'Hare, Neil; Smeaton, Alan F.; Czirjék, Csaba; O'Connor, Noel E.; Murphy, Noel
A generic news story segmentation system and its evaluation
(2004)
O'Hare, Neil; Smeaton, Alan F.; Czirjék, Csaba; O'Connor, Noel E.; Murphy, Noel
Abstract:
The paper presents an approach to segmenting broadcast TV news programmes automatically into individual news stories. We first segment the programme into individual shots, and then a number of analysis tools are run on the programme to extract features to represent each shot. The results of these feature extraction tools are then combined using a support vector machine trained to detect anchorperson shots. A news broadcast can then be segmented into individual stories based on the location of the anchorperson shots within the programme. We use one generic system to segment programmes from two different broadcasters, illustrating the robustness of our feature extraction process to the production styles of different broadcasters.
http://doras.dcu.ie/242/
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A hybrid technique for face detection in color images
(2005)
Cooray, Saman H.; O'Connor, Noel E.
A hybrid technique for face detection in color images
(2005)
Cooray, Saman H.; O'Connor, Noel E.
Abstract:
In this paper, a hybrid technique for face detection in color images is presented. The proposed technique combines three analysis models, namely skin detection, automatic eye localization, and appearance-based face/nonface classification. Using a robust histogram-based skin detection model, skin-like pixels are first identified in the RGB color space. Based on this, face bounding-boxes are extracted from the image. On detecting a face bounding-box, approximate positions of the candidate mouth feature points are identified using the redness property of image pixels. A region-based eye localization step, based on the detected mouth feature points, is then applied to face bounding-boxes to locate possible eye feature points in the image. Based on the distance between the detected eye feature points, face/non-face classification is performed over a normalized search area using the Bayesian discriminating feature (BDF) analysis method. Some subjective evaluation results are presented on ...
http://doras.dcu.ie/235/
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A note on feature selection for polyp detection in CT colonography
(2006)
Chowdhury, Tarik A.; Ghita, Ovidiu; Whelan, Paul F.; Miranda, Abhilash A.
A note on feature selection for polyp detection in CT colonography
(2006)
Chowdhury, Tarik A.; Ghita, Ovidiu; Whelan, Paul F.; Miranda, Abhilash A.
Abstract:
In this paper we describe a computer aided detection (CAD) algorithm for robust detection of polyps in computed tomography (CT) colonography. The devised algorithm identifies suspicious polyp candidate surfaces using the surface normal intersection, Hough transform, 3D histogram analysis, region growing and a convexity test. From these detected surfaces we extract statistical and morphological features in order to evaluate if the surface in question is a polyp or fold. In order to devise the optimal classification scheme the performance of two different classifiers are evaluated when the algorithm is applied to synthetic and real patient data. The experimental results indicate that the overall polyp detection performance shows sensitivity higher than 92% for polyps larger than 5mm with an average of 4.7 to 6.0 false positives per dataset
http://doras.dcu.ie/4642/
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A statistical approach for robust polyp detection in CT colonography
(2005)
Chowdhury, Tarik A.; Ghita, Ovidiu; Whelan, Paul F.
A statistical approach for robust polyp detection in CT colonography
(2005)
Chowdhury, Tarik A.; Ghita, Ovidiu; Whelan, Paul F.
Abstract:
In this paper we describe the development of a computationally efficient computer-aided detection (CAD) algorithm based on the statistical features derived from the local colonic surface that are used for the detection of colonic polyps in computed tomography (CT) colonography. The candidate surface voxels were detected and clustered using the surface normal intersection, convexity test, region growing and Hough transform. The main objective of this paper is the selection of the statistical features that optimally capture the convexity of the candidate surface and consequently provide a high discrimination between local surfaces defined by polyps and folds. The developed polyp detection scheme is computationally efficient (typically takes 3.9 minute per dataset) and shows 100% sensitivity for phantom polyps greater than 5 mm and 87.5% sensitivity for real polyps greater than 5 mm with an average of 4.05 false positives per dataset
http://doras.dcu.ie/4671/
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Action localization in video using a graph-based feature representation
(2017)
Jargalsaikhan, Iveel; Little, Suzanne; O'Connor, Noel E.
Action localization in video using a graph-based feature representation
(2017)
Jargalsaikhan, Iveel; Little, Suzanne; O'Connor, Noel E.
Abstract:
We propose a new framework for human action localization in video sequences. The option to not only detect but also localize actions in surveillance video is crucial to improving system's ability to manage high volumes of CCTV. In the approach, the action localization task is formulated the maximum-path finding problem in the directed spatio-temporal video-graph. The graph is constructed on the top of frame and temporal-based low-level features. To localize actions in the video-graph, we apply a maximum-path algorithm to find the path in the graph that is considered to be the localized action in the video. The proposed approach achieves competitive performance with the J-HMDB and the UCF-Sports dataset.
http://doras.dcu.ie/21832/
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Authentication based on face recognition under uncontrolled conditions
(2017)
Tavakolian, Niloofar; Nazemi, Azadeh; Azimifar, Zohreh
Authentication based on face recognition under uncontrolled conditions
(2017)
Tavakolian, Niloofar; Nazemi, Azadeh; Azimifar, Zohreh
Abstract:
This paper describes a method to address is- sues regarding uncontrolled conditions in face recognition. This method using mask projection, extracts affecting factor from the test sample and adds it to all normal training samples then compares test sample with all synthetic affected training samples. The method has been applied for multi-factor authentication/verification based on face biometric. Obtained results indicate high accuracy in the lake of sufficient training samples for each class(single sample classes). of the claimed user.
http://doras.dcu.ie/23042/
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Biologically-inspired data decorrelation for hyperspectral imaging
(2011)
Picon, Artzai; Ghita, Ovidiu; Rodriguez-Vaamonde, Sergio; Iriondo, Pedro M.; Whelan, Pa...
Biologically-inspired data decorrelation for hyperspectral imaging
(2011)
Picon, Artzai; Ghita, Ovidiu; Rodriguez-Vaamonde, Sergio; Iriondo, Pedro M.; Whelan, Paul F.
Abstract:
Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors) is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA), linear discriminant analysis (LDA), wavelet decomposition (WD), or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral) characteristics associated with the analyzed materials. The major objective of this article is to in...
http://doras.dcu.ie/18576/
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Cellular tracking in time-lapse phase contrast images
(2009)
Thirusittampalam, Ketheesan; Hossain, M. Julius; Ghita, Ovidiu; Whelan, Paul F.
Cellular tracking in time-lapse phase contrast images
(2009)
Thirusittampalam, Ketheesan; Hossain, M. Julius; Ghita, Ovidiu; Whelan, Paul F.
Abstract:
The quantitative analysis of live cells is a key issue in evaluating biological processes. The current clinical practice involves the application of a tedious and time consuming manual tracking procedure on large amount of data. As a result, automatic tracking systems are currently developed and evaluated. However, problems caused by cellular division, agglomeration, Brownian motion and topology changes are difficult issues that have to be accommodated by automatic tracking techniques. In this paper, we detail the development of a fully automated multi-target tracking system that is able to deal with Brownian motion and cellular division. During the tracking process our approach includes the neighbourhood relationship and motion history to enforce the cellular tracking continuity in the spatial and temporal domain. The experimental results reported in this paper indicate that our method is able to accurately track cellular structures in time-lapse data.
http://doras.dcu.ie/15571/
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Clustering-based analysis of semantic concept models for video shots
(2006)
Koskela, Markus; Smeaton, Alan F.
Clustering-based analysis of semantic concept models for video shots
(2006)
Koskela, Markus; Smeaton, Alan F.
Abstract:
In this paper we present a clustering-based method for representing semantic concepts on multimodal low-level feature spaces and study the evaluation of the goodness of such models with entropy-based methods. As different semantic concepts in video are most accurately represented with different features and modalities, we utilize the relative model-wise confidence values of the feature extraction techniques in weighting them automatically. The method also provides a natural way of measuring the similarity of different concepts in a multimedia lexicon. The experiments of the paper are conducted using the development set of the TRECVID 2005 corpus together with a common annotation for 39 semantic concepts
http://doras.dcu.ie/227/
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Continuous recognition of motion based gestures in sign language
(2009)
Kelly, Daniel; McDonald, John; Markham, Charles
Continuous recognition of motion based gestures in sign language
(2009)
Kelly, Daniel; McDonald, John; Markham, Charles
Abstract:
We present a novel and robust system for recognizing two handed motion based gestures performed within continuous sequences of sign language. While recognition of valid sign sequences is an important task in the overall goal of machine recognition of sign language, detection of movement epenthesis is important in the task of continuous recognition of natural sign language. We propose a framework for recognizing valid sign segments and identifying movement epenthesis. Our system utilizes a single HMM threshold model, per hand, to detect movement epenthesis. Further to this, we develop a novel technique to utilize the threshold model and dedicated gesture HMMs to recognize gestures within continuous sign language sentences. Experiments show that our system has a gesture detection ratio of 0.956 and a reliability measure of 0.932 when spotting 8 different signs from 240 video clips.
http://mural.maynoothuniversity.ie/8340/
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Editorial: Recent advances in image and video retrieval
(2005)
O'Connor, Noel E.
Editorial: Recent advances in image and video retrieval
(2005)
O'Connor, Noel E.
http://doras.dcu.ie/2195/
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Event detection in field sports video using audio-visual features and a support vector machine
(2005)
Sadlier, David A.; O'Connor, Noel E.
Event detection in field sports video using audio-visual features and a support vector machine
(2005)
Sadlier, David A.; O'Connor, Noel E.
Abstract:
In this paper, we propose a novel audio-visual feature-based framework for event detection in broadcast video of multiple different field sports. Features indicating significant events are selected and robust detectors built. These features are rooted in characteristics common to all genres of field sports. The evidence gathered by the feature detectors is combined by means of a support vector machine, which infers the occurrence of an event based on a model generated during a training phase. The system is tested generically across multiple genres of field sports including soccer, rugby, hockey, and Gaelic football and the results suggest that high event retrieval and content rejection statistics are achievable.
http://doras.dcu.ie/254/
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Extraction of epi-cardium contours from unseen images using a shape database
(2004)
Lynch, Michael; Ghita, Ovidiu; Whelan, Paul F.
Extraction of epi-cardium contours from unseen images using a shape database
(2004)
Lynch, Michael; Ghita, Ovidiu; Whelan, Paul F.
Abstract:
Accurate segmentation of the myocardium in cardiac magnetic resonance images can be restricted by image noise and low discrimination between the epi-cardium boundary and other organs. Segmentation of the epi-cardium is important for the calculation of left ventricle mass. In this paper we propose a novel method of epi-cardium segmentation, which firstly segments the left ventricle cavity. The epi-cardium boundary is found using the edge information in the image, and where such information is lacking it enhances the shape with the best fitting scaled segment, taken from a database of expertly assisted hand segmented images. In the final stage the segments are connected using a natural closed spline. The method was evaluated using a leave-one-out strategy on 24 volumes and calculates the coefficient of determination as 0.93 and a root mean square of the point to curve error of 1.54 mm when compared to manually segmented images.
http://doras.dcu.ie/15575/
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Extraction of fingerprint from regular expression for efficient prefiltering
(2009)
Wang, Xiaofei; Jiang, Junchen; Lin, Wei; Tang, Yi; Wang, Xiaojun; Liu, Bin
Extraction of fingerprint from regular expression for efficient prefiltering
(2009)
Wang, Xiaofei; Jiang, Junchen; Lin, Wei; Tang, Yi; Wang, Xiaojun; Liu, Bin
Abstract:
Deep packet inspection at high speed has become extremely important due to its application in a wide range of network applications, such as network security and network monitoring. Network intrusion detection system (NIDS) uses a collection of signatures of known security threats and viruses to scan the payload of each packet. Signatures are often specified in the form of regular expressions (regex), called patterns, which are traditionally implemented as finite automata. Deterministic finite automata (DFA) is fast, but requires prohibitive amounts of memory which limits their practical use. Instead of matching an incoming packet with each individual regex in a ruleset, we match the packet with a fixed substring, called fingerprint, of a regex first. Fixed string matching is faster and consumes less energy than regex matching. The fact is that if a packet does not match with the fingerprint of a regex, it will not match the regex itself. So fingerprints can be used in a prefilter en...
http://doras.dcu.ie/15528/
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Físchlár: an on-line system for indexing and browsing broadcast television content
(2001)
O'Connor, Noel E.; Marlow, Seán; Murphy, Noel; Smeaton, Alan F.; Browne, Paul; Dea...
Físchlár: an on-line system for indexing and browsing broadcast television content
(2001)
O'Connor, Noel E.; Marlow, Seán; Murphy, Noel; Smeaton, Alan F.; Browne, Paul; Deasy, Seán; Lee, Hyowon; McDonald, Kieran
Abstract:
This paper describes a demonstration system which automatically indexes broadcast television content for subsequent non-linear browsing. User-specified television programmes are captured in MPEG-1 format and analysed using a number of video indexing tools such as shot boundary detection, keyframe extraction, shot clustering and news story segmentation. A number of different interfaces have been developed which allow a user to browse the visual index created by these analysis tools. These interfaces are designed to facilitate users locating video content of particular interest. Once such content is located, the MPEG-1 bitstream can be streamed to the user in real-time. This paper describes both the high-level functionality of the system and the low-level indexing tools employed, as well as giving an overview of the different browsing mechanisms employed
http://doras.dcu.ie/249/
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Fusion of camera images and laser scans for wide baseline 3D scene alignment in urban environments
(2011)
Yang, Michael Ying; Cao, Yanpeng; McDonald, John
Fusion of camera images and laser scans for wide baseline 3D scene alignment in urban environments
(2011)
Yang, Michael Ying; Cao, Yanpeng; McDonald, John
Abstract:
In this paper we address the problem of automatic laser scan registration in urban environments. This represents a challenging problem for two major reasons. First, two individual laser scans might be captured at significantly changed viewpoints (wide baseline) and have very little overlap. Second, man-made buildings usually contain many structures of similar appearances. This will result in considerable aliasing in the matching process. By sensor fusion of laser data with camera images, we propose a novel improvement to the existing 2D feature techniques to enable automatic 3D alignment between two widely separated scans. The key idea consists of extracting dominant planar structures from 3D point clouds and then utilizing the recovered 3D geometry to improve the performance of 2D image feature for wide baseline matching. The resulting feature descriptors become more robust to camera viewpoint changes after the procedure of viewpoint normalization. Moreover, the viewpoint normalize...
http://mural.maynoothuniversity.ie/12373/
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Incorporating Facial Features into a Multi-Channel Gesture Recognition System for the Interpretation of Irish Sign Language Sequences
(2009)
Kelly, Daniel; Delannoy, Jane Reilly; McDonald, John; Markham, Charles
Incorporating Facial Features into a Multi-Channel Gesture Recognition System for the Interpretation of Irish Sign Language Sequences
(2009)
Kelly, Daniel; Delannoy, Jane Reilly; McDonald, John; Markham, Charles
Abstract:
In this paper we present a novel gesture recognition system for the interpretation of Irish Sign Language sequences which incorporates manual and non-manual information. We implement a set of independent Hidden Markov Model networks to recognize hand gestures, head movements and facial features into a single framework for interpreting Irish Sign Language. This framework is not specific to any particular type of gesture and we demonstrate this by showing that manual and non manual signals can be robustly spotted and classified from with continuous sign sequences.
http://mural.maynoothuniversity.ie/8336/
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Integration of feature distributions for colour texture segmentation
(2004)
Nammalwar, Padmapriya; Ghita, Ovidiu; Whelan, Paul F.
Integration of feature distributions for colour texture segmentation
(2004)
Nammalwar, Padmapriya; Ghita, Ovidiu; Whelan, Paul F.
Abstract:
This paper proposes a new framework for colour texture segmentation and determines the contribution of colour and texture. The distributions of colour and texture features provides the discrimination between different colour textured regions in an image. The proposed method was tested using different mosaic and natural images. From the results, it is evident that the incorporation of colour information enhanced the colour texture segmentation and the developed framework is effective.
http://doras.dcu.ie/4640/
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Measuring concept similarities in multimedia ontologies: analysis and evaluations
(2007)
Koskela, Markus; Smeaton, Alan F.; Laaksonen, J.
Measuring concept similarities in multimedia ontologies: analysis and evaluations
(2007)
Koskela, Markus; Smeaton, Alan F.; Laaksonen, J.
Abstract:
The recent development of large-scale multimedia concept ontologies has provided a new momentum for research in the semantic analysis of multimedia repositories. Different methods for generic concept detection have been extensively studied, but the question of how to exploit the structure of a multimedia ontology and existing inter-concept relations has not received similar attention. In this paper, we present a clustering-based method for modeling semantic concepts on low-level feature spaces and study the evaluation of the quality of such models with entropy-based methods. We cover a variety of methods for assessing the similarity of different concepts in a multimedia ontology. We study three ontologies and apply the proposed techniques in experiments involving the visual and semantic similarities, manual annotation of video, and concept detection. The results show that modeling inter-concept relations can provide a promising resource for many different application areas in semant...
http://doras.dcu.ie/251/
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Mobile mapping for the automated analysis of road signage and delineation
(2008)
McLoughlin, S.; Deegan, C.; Mulvihill, C.; Fitzgerald, C.; Markham, Charles
Mobile mapping for the automated analysis of road signage and delineation
(2008)
McLoughlin, S.; Deegan, C.; Mulvihill, C.; Fitzgerald, C.; Markham, Charles
Abstract:
A portable mobile stereo vision system designed for the assessment of road signage and delineation (lines and road studs or 'cat eyes') in low light conditions is presented. This novel system allows both geometric and photometric measurements to be made on objects in a scene. Using the system, it has been shown that retro-reflectors, and in particular road signs, can be identified by nature of their reflective properties. In addition, a novel imaging application has been investigated that facilitates the detection of defective road studs. Any objects examined can also be positioned on a national grid through the fusion of stereo vision with global positioning system technology. Automated feature extraction and analysis routines make the system fully autonomous.
http://mural.maynoothuniversity.ie/8352/
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Predicting organic acid concentration from UV/vis spectrometry measurements – A comparison of machine learning techniques
(2011)
Wolf, Christian; Gaida, Daniel; Stuhlsatz, Andre; Ludwig, Thomas; McLoone, Sean F.; Bon...
Predicting organic acid concentration from UV/vis spectrometry measurements – A comparison of machine learning techniques
(2011)
Wolf, Christian; Gaida, Daniel; Stuhlsatz, Andre; Ludwig, Thomas; McLoone, Sean F.; Bongards, Michael
Abstract:
The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and...
http://mural.maynoothuniversity.ie/3868/
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Quick sift(QSIFT), an approach to reduce SIFT computational cost
(2018)
Fazel, Zahra; Famouri, Mahmoud; Nazemi, Azadeh; Azimifar, Zohreh
Quick sift(QSIFT), an approach to reduce SIFT computational cost
(2018)
Fazel, Zahra; Famouri, Mahmoud; Nazemi, Azadeh; Azimifar, Zohreh
Abstract:
SIFT has been proven to be the most robust local rotation and illumination invariant feature descriptor. Being fully scale invariant is the most important advantage of this descriptor. The major drawback of SIFT is time complexity which prevents utilizing SIFT in real-time applications. This paper describes a method to increase the speed of SIFT feature extraction using keypoint estimation and approximation instead of keypoint calculation in various scales. This research attempts to decrease SIFT computational cost without sacrificing performance and propose quick SIFT method (QSIFT). The recent researches in this area have approved that direct feature value computation is more expensive than the value extrapolation. Consequently, the contribution of this research is to reduces the time execution without losing accuracy.
http://doras.dcu.ie/23502/
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Rhythm detection for speech-music discrimination in MPEG compressed domain
(2002)
Jarina, Roman; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
Rhythm detection for speech-music discrimination in MPEG compressed domain
(2002)
Jarina, Roman; O'Connor, Noel E.; Marlow, Seán; Murphy, Noel
Abstract:
A novel approach to speech-music discrimination based on rhythm (or beat) detection is introduced. Rhythmic pulses are detected by applying a long-term autocorrelation method on band-passed signals. This approach is combined with another, in which the features describe the energy peaks of the signal. The discriminator uses just three features that are computed from data directly taken from an MPEG-1 bitstream. The discriminator was tested on more than 3 hours of audio data. Average recognition rate is 97.7%.
http://doras.dcu.ie/246/
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