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Older Projects

Image Based Relighting

Efficient Light Field based CameraWalk (Biswarup Choudhury and Aviral Pandey): The light field rendering method is an interesting variation on achieving realism. Once authentic imagery has been acquired using a camera gantry, or a handheld camera, detailed novel views can be synthetically generated from various viewpoints. One common application of this technique is when a user “walks” through a virtual world. In this situation, only a subset of the previously stored light field is required, and considerable computation burden is encountered in processing the input light field to obtain this subset. In this paper, we show that appropriate portions of the light field can be cached at select “nodal points” that depend on the camera walk. Once spartanly and quickly cached, scenes can be rendered from any point on the walk efficiently. Efficient Image Updates using Lightfields (Biswarup Choudhury and Aviral Pandey): The light field rendering method is an interesting variation on achieving realism. Once authentic imagery has been acquired using a camera gantry, or a handheld camera, detailed novel views can be synthetically generated from various viewpoints. One common application of this technique is when a user “walks” through a virtual world. In this situation, only a subset of the previously stored light field is required, and considerable computation burden is encountered in processing the input light field to obtain this subset. In this paper, we show that appropriate portions of the light field can be cached at select “nodal points” that depend on the camera walk. Once spartanly and quickly cached, scenes can be rendered from any point on the walk efficiently. Image Based Rendering: (N N Kalyan) The process of modelling appearance and dynamics of the real world is quite complex and has produced compelling imagery in computer graphics.unfortunately the curent geometry based methods have several drawbacks. recently models directly from photographs has received more interest as they have an advantage in producing photo-realistic images from image inputs.This is called image-based rendering.However,this also suffers from few disadvantages.There are many algorithms for image-based rendering and there are also many hybrid appoaches which draw strength from both geometry-based and image-based renderings.The seminar basically deals with the techniques of rendering photorealistic images.

A Survey of Image-Based Relighting Techniques (Biswarup Choudhury): Image-based Relighting (IBRL) has recently attracted a lot of research interest for its ability to relight real objects or scenes, from novel illuminations captured in natural/synthetic environments. Complex lighting effects such as subsurface scattering, interreflection, shadowing, mesostructural self-occlusion, refraction and other relevant phenomena can be generated using IBRL. The main advantage of Image-based graphics is that the rendering time is independent of scene complexity as the rendering is actually a process of manipulating image pixels, instead of simulating light transport. The goal of this paper is to provide a complete and systematic overview of the research in Image-based Relighting. We observe that essentially all IBRL techniques can be broadly classified into three categories, based on how the scene/illumination information is captured: Reflectance function based, Basis function based, and Plenoptic function based. We discuss the characteristics of each of these categories and their representative methods. We also discuss about sampling density and types of light source, relevant issues of IBRL.

Motion Capture

Vision-Based Posing of 3D Virtual Actors (Ameya Vaidya and Appu Shaji): Construction of key poses is one of the most tedious and time consuming steps in synthesizing of 3D virtual actors. Recent alternate schemes expect the user to specify two inputs. Along with a neutral 3D reference model, more intuitive 2D inputs such as sketches, photographs or video frames are provided. Using these, of all the possible configurations, the “best” 3D virtual actor is posed. In this workr, we provide a solution to this ill-posed problem. We first give a solution to the problem of finding an approximate view consistent with the 2D sketch. Elements of this rigid-body solution are novel. Next, we provide a new solution to the process of extending or retracting limbs to more accurately suit the sketch. This posing algorithm, is based on a search based scheme inspired by anthropometric evidence. Less physical work is required by the actor to reach the desired pose from the base position. We also show that our algorithm converges to an acceptable solution much faster compared to the previous methods.

Markerless Motion Capture from Monocular Videos (Vishal Mamania & Appu Shaji): Motion capture has attracted a lot of attention in recent times because fits power to generate large quantities of realistic animation economically and relatively quickly. The data so acquired is being used in a variety of situations, notably commercial movies and games. Most of this work is done in the motion capture studios in a very controlled environment. In this work, we generalize the motion capture environment. Specifically, we perform the motion capture of Bharatanatyam. The proposed method uses domain specific knowledge to track major joints of the human in motion from the two-dimensional input data. We then make use of various physical and motion constraints regarding the human body to construct a set of feasible 3D poses. A graph based approach is used to find an optimal sequence of feasible poses that represents the original motion in the video.

Grafting Locomotive Motion (Shrinath Shanbaug): The notion of transplanting limbs to enhance a motion capture database is appealing and has been recently introduced. A key difficulty in the process is identifying believable combinations. Not all transplantations are successful; we also need to identify appropriate frames in the different clips that are cutpasted. In this paper, we describe motion grafting, a method to synthesize new believable motion using existing motion captured data. In our deterministic scheme designed for locomotive actions, motion grafts increase the number of combinations by mixing independent kinematics chains with a base motion in a given clip. Our scheme uses a cluster graph data structure to establish correlation among grafts so that the result is believable and synchronized.

Search and Transitioning for Motion Captured Sequences (Shrinath Shanbaug & Suddha Basu): Animators today have started using motion captured (mocap) sequences to drive characters. Mocap allows rapid acquisition of highly realistic animation data. Consequently animators have at their disposal an enormous amount of mocap sequences which ironically has created a new retrieval problem. Thus, while working with mocap databases, an animator often needs to work with a subset of useful clips. Once the animator selects a candidate working set of motion clips, she then needs to identify appropriate transition points amongst these clips for maximal reuse. In this paper, we describe methods for querying mocap databases and identifying transitions for a given set of clips. We preprocess clips (and clip subsequences), and precompute frame locations to allow interactive stitching. In contrast with existing methods that view each individual clips as nodes, for optimal reuse, we reduce the granularity.

Synthesizing New Walk and Climb Motions from a Single Motion Captured Walk Sequence (Shrinath Shanbaug): We describe a method to dynamically synthesize believable, variable stride, and variable foot lift motions for human walks and climbs. Our method is derived from a single motion captured walk sequence, and is guided by a simple kinematic walk model. The method allows control in the form of stride and lift parameters. It generates a range of variations while maintaining individualistic nuances of the captured performance.

Projector Camera Systems

Projector-camera based Solutions for Simulation System (Nilesh Heda): Projector based display systems are widely used as they offer an attractive combination of dense pixels over large regions. Traditionally, the projector is used for presentation purposes on single planar surface. However, it can be used for displaying on multi planar irregular surfaces. In this work, we discuss methods to use a projector along with a camera for displaying on irregular surfaces using projector-camera homography. In particular we would like to develop a shooting-range simulator system, using projector-camera system and laser pointer based interaction.

Signal Processing of Medical Diagnostic Data

Arrhythmia classification using local h'older exponents and support vector machine (Aniruddha Joshi) We proposed a novel hybrid Holder-SVM detection algorithm for arrhythmia classification. The performance was evaluated using benchmark MIT-BIH arrhythmia database. Accuracy of around 96% was achieved. The distinct scaling properties of different types of heart rhythms may be of clinical importance. Data Mining in Biomedical Signals (Aniruddha Joshi): This projects Works in Arrhythmia Classification problem, in which classifying 12 classes of Arrhythmias (including normal) using Local Holder Exponents and Support Vector Machines has been completed. This project currently aims at computerizing Indian Ayurveda technique, “Pulse Diagnosis”, to analyze the behavior of 'Arterial Pulse' according to age, some specific disorders and so on.

5th International Seminar on Ayurvedic education, research and drug standardization (Aniruddha Joshi): The “Nadi” or pulse has been used as a fundamental tool for diagnosis in “Ayurveda”. We provided a systematic measurement scheme to establish an objective diagnosis. The pulse waveforms show different rhythms, intensities, frequncy contents in normals and disorders considered, and thus is capable of classified by contempory machine learning algorithms.

Video Analysis

Content-Based Video Retrieval (Satwik Hebbar): Automatic content based schemes, as opposed to human endeavor, have become important as users attempt to organize massive data presented in the form of multimedia data such as home or movie videos. One important goal, be it in shot detection, or scene detection, or compression is the ability to find the foreground pixels. This higher level task benefits from a graph-based description of the video. The normalized cut framework is appealing because it looks at the video from a global perspective. Unfortunately due to quadratic storage and time complexity, the algorithm appears to be infeasible to use on large videos. In this work, we combine a local approach that promises a good segmentation [1] with the normalized cut approach [2] and make graph based schemes tractable.

Video Shot-Detection Using Learning Techniques (M. Nithya): Video has become an interactive medium of communication in everyday life. The sheer volume of video makes it extremely difficult to browse through and find the required information. Without knowing about its content, it is difficult to search the video. Manually analyzing the contents and indexing them is time consuming. The apparent alternative is to detect some events in the video automatically. The first step in automating the system is hot-detection which breaks the massive volume of video into smaller chunks called shots. This project aims in identifying shots.

Miscellaneous

3d File-format converter (Veerendra Singh): It converts standard Openflight File-format to Coin3D file-format. My role in the porject was to import Degree-Of-Freedom feature from OpenFlight to Coin3D format.

Radiosity (Alap Karapurkar): Global illumination enables production of pictures that look less like those synthesized by computers. The methods advance our knowledge of the physical environment such as the simulation of light transport. The fast multipole method is a promising method for achieving fast solutions to many applied problems in engineering, biology, computer vision, and statistics. It has been called one of the ten most significant numerical algorithms discovered in the 20th century, and won its inventors, Vladimir Rokhlin and Leslie Greengard, the Steele prize. The algorithm enables the product of restricted dense matrices with a vector to be evaluated in O(N) operations, when direct multiplication requires O(N

Global Illumination (Varun Singh): Global Illumination is the leading technology used today to produce more and more real looking synthetic pictures. The generation of an image by the radiosity method consumes large amounts of time and space. The environment or the scene to be rendered consists of surfaces divided into patches and we need to calculate the interaction between these patches.This equation essentially requires us to calculate an integration term for the form factor calculation between two patches. Monte Carlo algorithm provides an approximate method to calculate denite integrals.

Motion Segmentation (Abhishek Ranjan): Motion segmentation is a video analysis technique which aims at identifying and separating most prominently moving groups in a video. This technique has been used for solving various computer vision problems. Several approaches have been proposed to perform motion segmentation. An essential part of many of these approaches is analysis of frames of the video. Since these frames are images, image segmentation plays an important role in motion segmentation. In this project we have studied some of these approaches for motion and image segmentation. We concentrated on graph theoretic approaches to image segmentation.

Face Detection and Localisation (Abhineet Sawa): Automatic recognition of human face is a significatant problem in the development should accomplish the following tasks. For an arbitary picture determine whether it contains any faces. If so determine the number of faces as well as their posotion and size. Identify a person from his/her face. Make a description of facial expression.(Smile, Surpreise & so on). Make a description of each face. Find a certain face according to a given description. A first step in any face processing system is the detection from a single image is a challenging task because of variablity in scale, location, orientation, pose, facial expression, occlusion, and lighting conditions.