In this paper we propose to summarize videos based on key frames. We improve upon the histogram and pixel difference based approach with fuzzy rule based approach and also give a new approach which reduces the computa...
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ISBN:
(纸本)9781479915880
In this paper we propose to summarize videos based on key frames. We improve upon the histogram and pixel difference based approach with fuzzy rule based approach and also give a new approach which reduces the computation of framewise differences. We test our methods using fidelity ratio and compression ratio on videos of sports from YouTube and UCF sports dataset, videos of commercials and sitcoms. T he results of our methods are seen to be comparable to other state of the art approaches.
Bit Plane coding (BPC) constitutes an important component of the EBCOT Tier-1 block of JPEG2000 encoder. this paper proposes an efficient parallel hardware structure to implement the computation intensive word level b...
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ISBN:
(纸本)9781424442195
Bit Plane coding (BPC) constitutes an important component of the EBCOT Tier-1 block of JPEG2000 encoder. this paper proposes an efficient parallel hardware structure to implement the computation intensive word level bit plane coding algorithm. the proposed architecture computes the context and decision for all bit planes in parallel. the three coding passes are merged for all bit planes in a scan while the samples are coded in sequence. the proposed parallel BPC architecture offers a speed of 31 over the serial BPC architecture. Its memory requirement is independent of the size of the codeblock. the speed of the proposed architecture has been shown to be significantly faster than an architecture which has been recently reported in literature. the system architecture has been functionally verified by ModelSim and synthesized by TSMC 0.25 mu m vtvt CMOS cell libraries.
this paper is aimed at exploring the potential of using discriminatory primitives containing words for the task of detecting skilled forgeries. We consider handwritten Devanagri documents for this work. We have obtain...
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ISBN:
(纸本)9781479915880
this paper is aimed at exploring the potential of using discriminatory primitives containing words for the task of detecting skilled forgeries. We consider handwritten Devanagri documents for this work. We have obtained experimental handwriting data from subjects who have contributed handwriting samples in their natural handwriting. Other authors are asked to imitate the writing style of the subjects to produce a skilled forgery sample. Most of the literature dealing with writer recognition focus on signatures and very few reports have addressed the problem of detecting forgeries for handwritten indian scripts. We also use multiple words based classification for the targeted task of forgery detection. Our experiments show encouraging results.
We present a novel learning-based framework for detecting interesting events in soccer videos. the input to the system is a raw soccer video. We have learning at three levels - learning to detect interesting low-level...
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ISBN:
(纸本)9781424442195
We present a novel learning-based framework for detecting interesting events in soccer videos. the input to the system is a raw soccer video. We have learning at three levels - learning to detect interesting low-level features from image and video data using Support Vector Machines (hereafter SVMs), and a hierarchical Conditional Random Field(hereafter CRF-) based methodology to learn the dependencies of mid-level features and their relation withthe low level features, and high level decisions ('interesting events') and their relation withthe mid-level features: all on the basis of training video data. Descriptors are spatio-temporal in nature - they can be associated with a region in an image or a set of frames. Temporal patterns of descriptors characterise an event. We apply this framework to parse soccer videos into Interesting (a goal or a goal miss) and Non-Interesting videos. We present results of numerous experiments in support of the proposed strategy.
Large space with many cameras require huge storage and computational power to process these data for surveillance applications. In this paper we propose a distributed camera and processing based face detection and rec...
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ISBN:
(纸本)9781479915880
Large space with many cameras require huge storage and computational power to process these data for surveillance applications. In this paper we propose a distributed camera and processing based face detection and recognition system which can generate information for finding spatiotemporal movement pattern of individuals over a large monitored space. the system is built upon Hadoop Distributed File System using map reduce programming model. A novel key generation scheme using distance based hashing technique has been used for distribution of the face matching task. Experimental results have established effectiveness of the technique.
this paper proposes efficient and robust methods for tracking a moving object at multiple spatial and temporal resolution levels. the efficiency comes from optimising the amounts of spatial and temporal data processed...
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ISBN:
(纸本)9781424442195
this paper proposes efficient and robust methods for tracking a moving object at multiple spatial and temporal resolution levels. the efficiency comes from optimising the amounts of spatial and temporal data processed. the robustness results from multi-level coarse-to-fine state-space searching. Tracking across resolution levels incurs a accuracy-versus-speed trade-off. For example, tracking at higher resolutions incurs greater processing cost, while maintaining higher accuracy in estimating the position of the moving object. We propose a novel spatial multi-scale tracker that tracks at the optimal accuracy-versus-speed operating point. Next, we relax this requirement to propose a multi-resolution tracker that operates at a minimum acceptable performance level. Finally, we extend these ideas to a multi-resolution spatio-temporal tracker We show results of extensive experimentation in support of the proposed approaches.
We propose a novel framework for object detection and localization in images containing appreciable clutter and occlusions. the problem is cast in a statistical hypothesis testing framework. the image under test is co...
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ISBN:
(纸本)9781424442195
We propose a novel framework for object detection and localization in images containing appreciable clutter and occlusions. the problem is cast in a statistical hypothesis testing framework. the image under test is converted into a set of local features using affine invariant local region detectors, described using the popular SIFT descriptor Due to clutter and occlusions, this set is expected to contain features which do not belong to the object. We sample subsets of local features from this set and test for the alternate hypothesis of object present against the null hypothesis of object absent. Further, we use a method similar to the recently proposed spatial scan statistic to refine the object localization estimates obtained from the sampling process. We demonstrate the results of our method on the two datasets TUD Motorbikes and TUD Cars. TUD Cars database has background clutter TUD Motorbikes dataset is recognized to have substantial variation in terms of scale, back-ground, illumination, viewpoint and occlusions.
this paper presents a novel method for discovery and recognition of hairstyles in a collection of colored face images. We propose the use of Agglomerative clustering for automatic discovery of distinct hairstyles. Our...
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ISBN:
(纸本)9781479915880
this paper presents a novel method for discovery and recognition of hairstyles in a collection of colored face images. We propose the use of Agglomerative clustering for automatic discovery of distinct hairstyles. Our method proposes automated approach for generation of hair, background and face-skin probability-masks for different hairstyle category without requiring manual annotation. the probability-masks based density estimates are subsequently applied for recognizing the hairstyle in a new face image. the proposed methodology has been verified with a synthetic dataset of approximately thousand images, randomly collected from the Internet.
In this paper we have proposed methods for restoration of artifacts called Partial Color Artifact(PCA) and Blotches which appear frequently in old video films. the PCA occurs due to partial loss of information in the ...
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ISBN:
(纸本)9781479915880
In this paper we have proposed methods for restoration of artifacts called Partial Color Artifact(PCA) and Blotches which appear frequently in old video films. the PCA occurs due to partial loss of information in the upper color layers of the video film. As the inner most color layer is unaffected, the information present in this inner most color layer of the film aids in the reconstruction of damaged pixels from previously reconstructed frames. In Blotch artifact the pixel information is completely lost. the proposed Blotch reconstruction method is based on sparse recovery of signals from small number of measurements. Our blotch reconstruction process is computationally efficient because the image is segmented into non overlapping blocks and reconstruction is done block wise.
this paper presents a camera model to deal with underwater scene reconstruction from multiple images. Effects due to change in path of light ray at the medium interface is modelled for a general medium with unknown re...
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ISBN:
(纸本)9781467385640
this paper presents a camera model to deal with underwater scene reconstruction from multiple images. Effects due to change in path of light ray at the medium interface is modelled for a general medium with unknown refractive index. Our model calculates the refractive index of the medium and simultaneously removes the geometric refraction effects in images using point correspondences in image pairs. With known internal parameters of the camera we find the external parameters of the camera and then 3-D reconstruction is obtained.
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