Retinal images are widely used to manually or automatically detect and diagnose many diseases. Due to the complex imaging setup, there is a large luminosity and contrast variability within and across images. Here, we ...
详细信息
ISBN:
(纸本)9781424442195
Retinal images are widely used to manually or automatically detect and diagnose many diseases. Due to the complex imaging setup, there is a large luminosity and contrast variability within and across images. Here, we use the knowledge of the imaging geometry and propose an enhancement method for colour retinal images, with a focus on contrast improvement with no introduction of artifacts. The method uses non-uniform sampling to estimate the degradation and derive a correction factor from a single plane. We also propose a scheme for applying the derived correction factor to enhance all the colour planes of a given image. The proposed enhancement method has been tested on a publicly available dataset [8]. Results show marked improvement over existing methods.
The proceedings contain 10 papers. The special focus in this conference is on computervision Applications. The topics include: AECNN: Autoencoder with Convolutional Neural Network for Hyperspectral image Classificati...
ISBN:
(纸本)9789811513862
The proceedings contain 10 papers. The special focus in this conference is on computervision Applications. The topics include: AECNN: Autoencoder with Convolutional Neural Network for Hyperspectral image Classification;optic Disc Segmentation in Fundus images Using Anatomical Atlases with Nonrigid Registration;bird Species Classification Using Transfer Learning with Multistage Training;a Deep Learning Paradigm for Automated Face Attendance;Robust Detection of Iris Region Using an Adapted SSD Framework;dynamic image Networks for Human Fall Detection in 360-degree Videos;image Segmentation and Geometric Feature Based Approach for Fast Video Summarization of Surveillance Videos;supervised Hashing for Retrieval of Multimodal Biometric Data.
In this paper a video coding scheme based on parametric compression of texture is proposed Each macro block is characterized either as an edge block, or as a non edge block containing texture. The non edge blocks are ...
详细信息
ISBN:
(纸本)9781424442195
In this paper a video coding scheme based on parametric compression of texture is proposed Each macro block is characterized either as an edge block, or as a non edge block containing texture. The non edge blocks are coded by modeling them as an auto-regressive process (AR). By applying the AR model in spatio-temporal domain, we ensure both spatial as well as temporal consistency. Edge blocks are encoded using the standard H.264/AVC. The proposed algorithm achieves upto 54.52% more compression as compared to the standard H.264/AVC at similar visual quality.
High-intensity activities in sports like basketball can result in fatigue without proper recovery. This study introduces a collaborative framework that leverages computervision (CV) and Machine Learning for evaluatin...
详细信息
ISBN:
(纸本)9798400710759
High-intensity activities in sports like basketball can result in fatigue without proper recovery. This study introduces a collaborative framework that leverages computervision (CV) and Machine Learning for evaluating jump landings and predicting athletic readiness by modelling Countermovement Jumps (CMJs) biomechanical aspects. Seventeen female collegiate basketball athletes of Sacred Heart University (SHU), CT, USA, participated in weekly CMJs over a 26-week season. Through CV-driven semantic analysis of videos, the framework identifies the crucial initial contact and maximum flexion point during jump landings and extracts kinetic and kinematic features of the lower extremities. Next, an inferential analysis is conducted to understand the relationship between these features and the CMJ-driven reactive strength indexmodified (RSImod) score, which measures fatigue and athletic readiness. An XGBoost regressor, trained on the past week's data, then predicted the RSImod score for the following week, which resulted in an MSE of 0.020 and an R-2 of 0.892. Using SHapley Additive exPlanations (SHAP), the framework offers interpretable feedback, aiding coaches in creating personalised training programs and optimising athletic performance while minimising injury risks.
We present a reduced model based on position based dynamics for real-time simulation of human musculature. We demonstrate our methods on the muscles of the human arm. Co-simulation of all the muscles of the human arm ...
详细信息
ISBN:
(纸本)9781450366151
We present a reduced model based on position based dynamics for real-time simulation of human musculature. We demonstrate our methods on the muscles of the human arm. Co-simulation of all the muscles of the human arm allow us to accurately track the development of stresses and strains in the muscles, when the arm is moved. We evaluate our method for accuracy by comparing it with gold standard simulation models based on finite volume methods, and demonstrate the stability of the method under flexion, extension and torsion.
Face frontalization is the process of synthesizing a frontal view of a face, given its non-frontal view. Frontalization is used in intelligent photo editing tools and also aids in improving the accuracy of face recogn...
详细信息
ISBN:
(纸本)9781467385640
Face frontalization is the process of synthesizing a frontal view of a face, given its non-frontal view. Frontalization is used in intelligent photo editing tools and also aids in improving the accuracy of face recognition systems. For example, in the case of photo editing, faces of persons in a group photo can be corrected to look into the camera, if they are looking elsewhere. Similarly, even though recent methods in face recognition claim accuracy which surpasses that of humans in some cases, performance of recognition systems degrade when profile view of faces are given as input. One way to address this issue is to synthesize frontal views of faces before recognition. We propose a simple and efficient method to address the face frontalization problem. Our method leverages the fact that faces in general have a definite structure and can be represented in a low dimensional subspace. We employ an exemplar based approach to find the transformation that relates the profile view to the frontal view, and use it to generate realistic frontalizations. Our method does not involve estimating 3D model of the face, which is a common approach in previous work in this area. This leads to an efficient solution, since we avoid the complexity of adding one more dimension to the problem. Our method also retains the structural information of the individual as compared to that of a recent method [4], which assumes a generic 3D model for synthesis. We show impressive qualitative and quantitative results in comparison to the state-of-the-art in this field.
Everyday spatio-temporal reasoning is driven through qualitative abstractions over mental maps or 'diagrams'. Diagrammatic reasoning involves direct manipulation and inspection of diagrams as the primary means...
详细信息
ISBN:
(纸本)9781467385640
Everyday spatio-temporal reasoning is driven through qualitative abstractions over mental maps or 'diagrams'. Diagrammatic reasoning involves direct manipulation and inspection of diagrams as the primary means of inference. Diagrammatic representation offer computational advantage in problems where spatial relationships play a prominent role. In video, objects change spatial relationships over time. Therefore, combining diagrammatic reasoning with qualitative spatial and temporal reasoning holds promise. In this paper, we put forward a framework combining diagrammatic representation with qualitative spatial and temporal reasoning for motion event detection in video. Key frames with tracked objects for a given video are extracted. These frames in forward moving time are represented using specified;'diagrams'. A set of perception function is defined exploiting results from diagrammatic reasoning and qualitative spatial and temporal reasoning for determining spatial relations between objects of interest. Inter diagrammatic reasoning operator is used to combine sequence of diagrams for extracting spatio-temporal changes. Diagram modification function is defined exploiting results from qualitative reasoning to extract directional information. Considering extracted relative position and relative direction of displacement as features, we use supervised machine learning techniques to recognize motion events in video. The approach is tested in videos with few people/groups meeting, walking together and splitting up/fighting from the CAVIAR dataset.
We propose a face recognition method that fuses information acquired from global and local features of the face for improving performance. Principle components analysis followed by Fisher analysis is used for dimensio...
详细信息
We propose a face recognition method that fuses information acquired from global and local features of the face for improving performance. Principle components analysis followed by Fisher analysis is used for dimensionality reduction and construction of individual feature spaces. Recognition is done by probabilistically fusing the confidence weights derived from each feature space. The performance of the method is validated on FERET and AR databases. (c) 2006 Elsevier B.V. All rights reserved.
Compressed sensing magnetic resonance imaging (CSMRI) have demonstrated that it is possible to accelerate MRI scan time by reducing the number of measurements in the k-space without significant loss of anatomical deta...
详细信息
ISBN:
(纸本)9781450347532
Compressed sensing magnetic resonance imaging (CSMRI) have demonstrated that it is possible to accelerate MRI scan time by reducing the number of measurements in the k-space without significant loss of anatomical details. The number of k-space measurements is roughly proportional to the sparsity of the MR signal under consideration. Recently, a few works on CSMRI have revealed that the sparsity of the MR signal can be enhanced by suitable weighting of different regularization priors. In this paper, we have proposed an efficient adaptive weighted reconstruction algorithm for the enhancement of sparsity of the MR image. Experimental results show that the proposed algorithm gives better reconstructions with less number of measurements without significant increase of the computational time compared to existing algorithms in this line.
This paper proposes a method for personal identification based on iris recognition. The iris segmentation is obtained by using an integro-differential operation. The segmented iris is then normalised and actually a sm...
详细信息
暂无评论