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Real-Time Rendering and Manipulation of Large Terrains

Real-Time Rendering and Manipulation of Large Terrains

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Shiben Bhattacharjee Suryakant Patidar P.J. Narayanan Center for Visual Information Technology International Institute of Information Technology Hyderabad India

Terrains are challenging geometric objects for real-time rendering and interactive manipulation. State-of-the-art terrain rendering systems use custom, multi-resolution, representations like geometry clipmaps for fast rendering on the GPU. In this paper, we present a system that exploits the power and flexibility of the modern GPUs to store, render, and manipulate terrains with minimal CPU involvement. The central idea is to use a regular-grid representation and fixed size blocks/tiles that change in resolution. The potentially visible portion of the terrain is cached at the highest necessary resolution and is rendered from the GPU. The CPU sends a light geometry template which is expanded by the Geometry Shader to the triangles, using the heights stored in the GPU Cache. The CPU performs a coarse culling of the tiles with the GPU performing fine culling. The GPU cache is updated continuously as the viewpoint changes. Our system enables the terrain to be modified procedurally or edited interactively on the GPU with no CPU involvement. The terrain can also interact with a large number of external objects in real-time entirely within the GPU. We achieve a consistent rendering rate of 100 frames per second with terrain modification and interactions as well as a triangle rate of upto 350 million per second on an Nvidia 8800 GTX GPU for large terrains, with a CPU load below 10%.

关键词： Geometry Rendering (computer graphics) Tiles Information technology Physics computer vision computer graphics image processing Aerospace simulation Geographic Information Systems

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Annotating Dance Posture images Using Multi Kernel Feature Combination

Annotating Dance Posture Images Using Multi Kernel Feature C...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Ehtesham Hassan Santanu Chaudhury M. Gopal Department of Electrical Engineering Indian Institute of Technology Delhi India

We present a novel dance posture based annotation model by combining features using Multiple Kernel Learning (MKL). We have proposed a novel feature representation which represents the local texture properties of the image. The annotation model is defined in the direct a cyclic graph structure using the binary MKL algorithm. The bag-of-words model is applied for image representation. The experiments have been performed on the image collection belonging to two indian classical dances (Bharatnatyam and Odissi). The annotation model has been tested using SIFT and the proposed feature individually and by optimally combining both the features. The experiments have shown promising results.

关键词： Kernel Vectors Support vector machines image representation Vocabulary image color analysis Feature extraction

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QAAD: Quality Aware Adaptive Denoising 11

QAAD: Quality Aware Adaptive Denoising

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11th IEEE International conference on Signal processing and Integrated Networks, SPIN 2024

作者： Parse, Tejas Ajay Awasthi, Tanishq Yadav, Dushyant Joshi, Piyush Indian Institute of Information Technology Department of Computer Science Sri City Chittoor India

ISBN: (纸本)9798350308433

image denoising is a fundamental task in computer vision and image processing, crucial for improving the visual quality and interpretability of images captured in noisy environments. In this research, we propose a quality-Aware adaptive denoising (QAAD) approach that leverages the Blind/Referenceless image Spatial Quality Evaluator (BRISQUE) as a key factor in determining the optimal denoising algorithm for an image. Our methodology involves an initial assessment of image quality using BRISQUE scores for a diverse set of images. Subsequently, we employ various image quality enhancement algorithms to enhance the image quality. Through extensive experimentation, we assess the performance of these enhancement algorithms with respect to specific ranges of BRISQUE scores. This evaluation enables us to determine which denoising algorithm performs optimally for images falling within particular BRISQUE score ranges. The innovation in our approach lies in its adaptability. When an image proceeds for denoising, its BRISQUE score is calculated and, based on this score, the most suitable denoising algorithm for that specific image is selected. This adaptive strategy ensures that the chosen denoising algorithm is tailored to the inherent noise characteristics of the input image, leading to superior denoising results. Our experimental results demonstrate the effectiveness of our approach in enhancing image quality and achieving state-of-The-Art denoising results. This research contributes to the field of image processing by providing a data-driven and adaptive solution for image denoising, ultimately enhancing the quality of images in diverse real-world applications. © 2024 IEEE.

关键词： image denoising

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Mandala as computational art: Vectorization and beyond 23

Mandala as computational art: Vectorization and beyond

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proceedings of the fourteenth indian conference on computer vision, graphics and image processing

作者： Tusita Sarkar Partha Bhowmick Department of Computer Science and Engineering IIT Kharagpur India

ISBN: (纸本)9798400716256

This paper introduces a novel technique of computational art with mandala—an iconic heritage of indian folk art. Its novelty lies in several fundamental steps. The first one is fixing the asymmetries and the imperfections in a hand-drawn piece of art based on the notion of a primitive map. The primitive map is described using a novel concept of geometric salience—a set of well-defined salient points on the frontier polygon of a primitive—characterizing the concavities and convexities present in the primitive. The primitive map is also used for the vectorization of a mandala and its succinct representation as a mandala sector graph (MSG), which eventually results in efficient graph operations on an existing artwork to create a new piece of art. The use of frontier polygons in different steps of the algorithm makes it robust and efficient. Experimental results on various datasets demonstrate the potential and versatility of the proposed technique.

关键词： Art and culture alpana art and psychology computational art digital art mandala vectorization.

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Towards Realistic Underwater Dataset Generation and Color Restorationg± 13

Towards Realistic Underwater Dataset Generation and Color Re...

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13th indian conference on computer vision, graphics, and image processing, ICVGIP 2022

作者： Jain, Neham Matta, Gopi Raju Mitra, Kaushik IIT Madras Tamil Nadu Chennai India

ISBN: (纸本)9781450398237

Recovery of true color from underwater images is an ill-posed problem. This is because the wide-band attenuation coefficients for the RGB color channels depend on object range, reflectance, etc. which are difficult to model. Also, there is backscattering due to suspended particles in water. Thus, most existing deep-learning based color restoration methods, which are trained on synthetic underwater datasets, do not perform well on real underwater data. This can be attributed to the fact that synthetic data cannot accurately represent real conditions. To address this issue, we use an image to image translation network to bridge the gap between the synthetic and real domains by translating images from synthetic underwater domain to real underwater domain. Using this multimodal domain adaptation technique, we create a dataset that can capture a diverse array of underwater conditions. We then train a simple but effective CNN based network on our domain adapted dataset to perform color restoration. Code and pre-trained models can be accessed at https://***/nehamjain10/TRUDGCR © 2022 ACM.

关键词： image reconstruction

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Learning Feature Trajectories Using Gabor Filter Bank for Human Activity Segmentation and Recognition

Learning Feature Trajectories Using Gabor Filter Bank for Hu...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Sunil Kumar Gupta Y. Senthil Kumar K.R. Ramakrishnan Indian Institute of Science Bangalore India

We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using dynamic time warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later. We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.

关键词： Gabor filters Humans Surveillance Videos Clustering algorithms computer vision image segmentation Application software Legged locomotion Hidden Markov models

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Parallel mesh regularization and resampling algorithm for improved mesh registration

Parallel mesh regularization and resampling algorithm for im...

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National conference on computer vision, Pattern Recognition, image processing and graphics (NCVPRIPG)

作者： Sumandeep Banerjee Somnath Dutta Prabir Kumar Biswas Partha Bhowmick Department of Electronics and Electrical Communication Engineering Department of Computer Science and Engineering Indian Institute of Technology Kharagpur

In this paper, we present a fast and efficient algorithm for regularization and resampling of triangular meshes generated by 3D reconstruction methods such as stereoscopy, laser scanning etc. We also present a scheme for efficient parallel implementation of the proposed algorithm and the time gain with increasing number of processor cores.

关键词： Three-dimensional displays Face Instruction sets Interpolation Equations Parallel algorithms Cameras

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An Evolutionary Based Slow and Fast Moving Video Object Detection Scheme Using Compound Markov Random Field Model

An Evolutionary Based Slow and Fast Moving Video Object Dete...

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indian conference on computer vision, graphics & image processing (ICVGIP)

作者： Badri Narayan Subudhi Pradipta Kumar Nanda Department of Electrical Engineering National Institute of Technology Rourkela India Department of Electonics and Telecommunication C. V. Raman College of Engineering Bhubaneswar India

We propose an evolving scheme to detect slow as well as fast moving objects in a video sequence. The proposed scheme employ both spatio-temporal and temporal segmentation to obtain the video object plane and hence detection. We propose a compound Markov random field model as the a priori image model that takes into account the spatial distribution of the current frame, temporal frames and the edge maps of the temporal frames. The spatio-temporal segmentation is cast as a pixel labeling problem and the labels are the MAP estimates. The MAP estimates of a frame are obtained by a hybrid algorithm. The spatial segmentation of a given frame evolves to generate the spatial segmentation of the subsequent frames. The evolved spatial segmentation together with the temporal segmentation produces the Video Object Plane (VOP) and hence detection. Our scheme does require the computation of spatio-temporal segmentation of the initial frame thus speeding up the whole process. The results of the proposed scheme are compared with JSEG method are found to be better in terms of the misclassification error.

关键词： Object detection Markov random fields image segmentation Video sequences Context modeling computer vision Stochastic processes Genetic algorithms Dissolved gas analysis computer graphics

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Improved low resolution heterogeneous face recognition using re-ranking 6th

Improved low resolution heterogeneous face recognition using...

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6th National conference on computer vision, Pattern Recognition, image processing and graphics, NCVPRIPG 2017

作者： Mudunuri, Sivaram Prasad Venkataramanan, Shashanka Biswas, Soma Department of Electrical Engineering Indian Institute of Science Bangalore India

ISBN: (纸本)9789811300196

Recently, near-infrared to visible light facial image matching is gaining popularity, especially for low-light and night-time surveillance scenarios. Unlike most of the work in literature, we assume that the near-infrared probe images have low-resolution in addition to uncontrolled pose and expression, which is due to the large distance of the person from the camera. To address this very challenging problem, we propose a re-ranking strategy which takes into account the relation of both the probe and gallery with a set of reference images. This can be used as an add-on to any existing algorithm. We apply it with one recent dictionary learning algorithm which uses alignment of orthogonal dictionaries. We also create a benchmark for this task by evaluating some of the recent algorithms for this experimental protocol. Extensive experiments are conducted on a modified version of the CASIA NIR VIS 2.0 database to show the effectiveness of the proposed re-ranking approach. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Face recognition

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Object extraction from image using higher order entropy

Object extraction from image using higher order entropy

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International conference on Pattern Recognition

作者： S.K. Pal N.R. Pal Electronics & Communication Sciences Unit Indian Statistical Institute Calcutta India Computer Sciences Unit Indian Statistical Institute Calcutta India

Entropy of order q (depending on the information contained in a sequence of gray levels of length q) and conditional entropy of an image are defined. Using these definitions, two algorithms are formulated and implemented with the help of its co-occurrence matrix. Their superiority for image thresholding (object-background classification) is established.< >

关键词： Entropy Signal processing algorithms image segmentation Histograms Classification algorithms Propellers computer vision graphics

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