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检索条件"任意字段=Proceedings of the Fourteenth Indian Conference on Computer Vision, Graphics and Image Processing"

共 1496 条记录，以下是591-600 订阅

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TraCount: A Deep Convolutional Neural Network for Highly Overlapping Vehicle Counting 16

TraCount: A Deep Convolutional Neural Network for Highly Ove...

引用

10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Surya, Shiv Babu, Venkatesh R. Indian Inst Sci Bangalore Karnataka India

ISBN: (纸本)9781450347532

We propose a novel deep framework, TraCount, for highly overlapping vehicle counting in congested traffic scenes. TraCount uses multiple fully convolutional(FC) sub-networks to predict the density map for a given static image of a traffic scene. The different FC sub-networks provide a range in size of receptive fields that enable us to count vehicles whose perspective effect varies significantly in a scene due to the large visual field of surveillance cameras. The predictions of different FC sub-networks are fused by weighted averaging to obtain a final density map. We show that TraCount outperforms the state of the art methods on the challenging TRANCOS dataset that has a total of 46796 vehicles annotated across 1244 images.

关键词： Convolutional neural networks deep learning vehicle counting

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Exposing Splicing Forgeries in Digital images through Dichromatic Plane Histogram Discrepancies 16

Exposing Splicing Forgeries in Digital Images through Dichro...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Mazumdar, Aniruddha Bora, Prabin Kumar Indian Inst Technol Guwahati Dept EEE Gauhati 781039 Assam India

ISBN: (纸本)9781450347532

One of the common image forgery techniques is the splicing, where parts from different images are copied and pasted onto a single image. This paper proposes a new forensics method for detecting splicing forgeries in images containing human faces. Our approach is based on extracting an illumination-signature from the faces of people present in an image using the dichromatic reflection model (DRM). The dichromatic plane histogram (DPH), which is calculated by applying the 2D Hough Transform on the face images, is used as the illumination-signature. The correlation measure is employed to compute the similarity between the DPHs obtained from different faces present in an image. Finally, a simple threshold on this similarity measure exposes splicing forgeries in the image. Experimental results show the efficacy of the proposed method.

关键词： image forensics Illumination Estimation Illumination-signature 2D HoughTransform

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Hierarchical Spectral Clustering based Large Margin Classification of Visually Correlated Categories 16

Hierarchical Spectral Clustering based Large Margin Classifi...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Bose, Digbalay Chaudhuri, Subhasis IBM Res Bangalore Karnataka India Indian Inst Technol Dept Elect Engn Bombay Maharashtra India

ISBN: (纸本)9781450347532

Object recognition is one of the challenging tasks in computer vision and the problem becomes increasingly difficult when the image categories are visually correlated among themselves i.e. they are visually similar and only fine differences exist among the categories. This paper has a two-fold objective which involves organization of the image categories in a hierarchical tree like structure using self tuning spectral clustering for exploiting the correlations among them. The organization phase is followed by a node specific large margin nearest neighbor classification scheme, where a Mahalnobis distance metric is learnt for each non-leaf node. Further a procedure for hyperparameters selection has been discussed w.r.t two strategies i.e. grid search and Bayesian optimization. The proposed algorithm's effectiveness is tested on selected classes of the popular imagenet dataset.

关键词： Object recognition Visually correlated categories Large margin nearest neighbor classification Self Tuning Spectral Clustering Hierarchical Organization

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Sketch-based Simulated Draping for indian Garments 16

Sketch-based Simulated Draping for Indian Garments

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Muralikrishnan, Sanjeev Chaudhuri, Parag Indian Inst Technol Dept Comp Scince & Engn Bombay 400076 Maharashtra India

ISBN: (纸本)9781450347532

Virtual garments like shirts and trousers are created from 2D patterns stitched over 3D models. However, indian garments, like dhotis and saris, pose a unique draping challenge for physically-simulated garment systems, as they are not stitched garments. We present a method to intuitively specify the parameters governing the drape of an indian garment using a sketch-based interface. We then interpret the sketch strokes to procedural, physically-simulated draping routines to wrap, pin and tuck the garments around the body mesh as needed. After draping, the garments are ready to be simulated and used during animation as required. We present several examples of our draping technique.

关键词： Automated garment draping indian garment draping sketch-based

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A Fast Identity-Independent Expression Recognition System for Robust Cartoonification using Smart Devices 16

A Fast Identity-Independent Expression Recognition System fo...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Agarwal, Gorisha Garg, Ronak Garg, Divya Prasad, Bikash Dutta, Tanima Gupta, Hari Prabhat Indian Inst Technol BHU Varanasi Varanasi Uttar Pradesh India

ISBN: (纸本)9781450347532

Facial expressions convey rich information about emotions, intentions and other internal states of a person. Automatic facial expression and cartoonification systems are aiming towards the application of computer vision systems in human computer interaction, emotion analysis, medical care, virtual learning and even entertainment. In this paper, we propose an identity-independent robust system to detect human expression and generate their corresponding cartoonified images in real-time using smart-devices. Identity-independent expression recognition system enhances the facial features of query face image using its intra-class variation image and classifies using support vector machines. The method is robust to variation in identity and illumination of the query face image. Along with the basic expressions, like angry, happy and sad, we have also successfully detected the emotional states of sleepy and pain. The experimental results on JAFFE, CK+, PICS, Yalefaces, and Senthil databases show the effectiveness of the system.

关键词： Emotion recognition facial expressions Cartoonification Human computer interaction Augumented reality

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Ghosting Free HDR for Dynamic Scenes via Shift-maps 16

Ghosting Free HDR for Dynamic Scenes via Shift-maps

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Prabhakar, K. Ram Babu, R. Venkatesh Indian Inst Sci Dept Computat & Data Sci Bangalore Karnataka India

ISBN: (纸本)9781450347532

Given a set of sequential exposures, High Dynamic Range imaging is a popular method for obtaining high-quality images for fairly static scenes. However, this typically suffers from ghosting artifacts for scenes with significant motion. Also, existing techniques cannot handle heavily saturated regions in the sequence. In this paper, we propose an approach that handles both the issues mentioned above. We achieve robustness to motion (both object and camera) and saturation via an energy minimization formulation with spatio-temporal constraints. The proposed approach leverages information from the neighborhood of heavily saturated regions to correct such regions. The experimental results demonstrate the superiority of our method over state-of-the-art techniques for a variety of challenging dynamic scenes.

关键词： Exposure Fusion High Dynamic Range imaging

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On The (Soccer) Ball 16

On The (Soccer) Ball

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Sanyal, Samriddha Kundu, Arnab Mukherjee, Dipti Prasad Indian Stat Inst 203 Barrackpore Trunk Rd Kolkata 700108 India

ISBN: (纸本)9781450347532

The problem of tracking ball in a soccer video is challenging because of sudden change in speed and orientation of the soccer ball. Successful tracking in such a scenario depends on the ability of the algorithm to balance prior constraints continuously against the evidence garnered from the sequences of images. This paper proposes a particle filter based algorithm that tracks the ball when it changes its direction suddenly or takes high speed. Exact, deterministic tracking algorithms based on discretized functional, suffer from severe limitations in the form of prior constraints. Our tracking algorithm has shown excellent result even for partial occlusion which is a major concern in soccer video. We have shown that the proposed tracking algorithm is at least 7.2% better compared to competing approaches for soccer ball tracking.

关键词： Tracking Soccer ball Particle filter Measurement space Resampling

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How Much Can A Gaussian Smoother Denoise? 16

How Much Can A Gaussian Smoother Denoise?

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Gubbi, Sagar Venkatesh Gupta, Ashutosh Seelamantula, Chandra Sekhar Indian Inst Sci Dept Elect Commun Engn Bangalore 560012 Karnataka India Indian Space Res Org Ahmadabad 380058 Gujarat India Indian Inst Sci Dept Elect Engn Bangalore 560012 Karnataka India

ISBN: (纸本)9781450347532

Recently, a suite of increasingly sophisticated methods have been developed to suppress additive noise from images. Most of these methods take advantage of sparsity of the underlying signal in a specific transform domain to achieve good visual or quantitative results. These methods apply relatively complex statistical modelling techniques to bifurcate the noise from the signal. In this paper, we demonstrate that a spatially adaptive Gaussian smoother could be a very effective solution to the image denoising problem. To derive the optimal parameter estimates for the Gaussian smoothening kernel, we derive and deploy a surrogate of the mean squared error (MSE) risk similar to the Stein's estimator for Gaussian distributed noise. However, unlike the Stein's estimator or its counterparts for other noise distributions, the proposed generic risk estimator (GenRE) uses only first- and second-order moments of the noise distribution and is agnostic to the exact form of the noise distribution. By locally adapting the parameters of the Gaussian smoother, we obtain a denoising function that has a denoising performance (quantified by the peak signal-to-noise ratio (PSNR)) that is competitive to far more sophisticated methods reported in the literature. To avail the parallelism offered by the proposed method, we also provide a graphics processing unit (GPU) based implementation.

关键词： image denoising Gaussian smoothing Stein's lemma generic risk estimation spatially varying smoothers graphics processing unit (GPU)

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Overlapping Cell Nuclei Segmentation in Microscopic images Using Deep Belief Networks 16

Overlapping Cell Nuclei Segmentation in Microscopic Images U...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Duggal, Rahul Gupta, Anubha Gupta, Ritu Wadhwa, Manya Ahuja, Chirag Indraprastha Inst Informat Technol Delhi Dept ECE SBILab New Delhi India AIIMS Dr BRA IRCH Lab Oncol Unit Delhi India Inst Informat Technol Delhi Dept CSE New Delhi India

ISBN: (纸本)9781450347532

This paper proposes a method for segmentation of nuclei of single/isolated and overlapping/touching immature white blood cells from microscopic images of B-Lineage acute lymphoblastic leukemia (ALL) prepared from peripheral blood and bone marrow aspirate. We propose deep belief network approach for the segmentation of these nuclei. Simulation results and comparison with some of the existing methods demonstrate the efficacy of the proposed method.

关键词： Overlapping nuclei segmentation B-ALL Deep Belief Network Machine Learning

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Robust Pedestrian Tracking using improved Tracking-Learning-Detection algorithm 16

Robust Pedestrian Tracking using improved Tracking-Learning-...

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10th indian conference on computer vision, graphics and image processing (ICVGIP)

作者： Verma, Ritika Sreedevi, Indu Delhi Technol Univ Delhi India

ISBN: (纸本)9781450347532

Manual analysis of pedestrians for surveillance of large crowds in real time applications is not practical. Tracking-Learning-Detection suggested by Kalal , Mikolajczyk and Matas [1] is one of the most prominent automatic object tracking system. TLD can track single object and can handle occlusion and appearance change but it suffers from limitations .In this paper, tracking of multiple objects and estimation of their trajectory is suggested using improved TLD. Feature tracking is suggested in place of grid based tracking to solve the limitation of tracking during out of plane rotation .This also leads to optimization of algorithm. Proposed algorithm also achieves auto-initialization with detection of pedestrians in the first frame which makes it suitable for real time pedestrian tracking.

关键词： Tracking-Learning-Detection Pedestrian tracking Visual tracking

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