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Multi Focus Structured Light for Recovering Scene Shape and Global Illumination [chapter]

Supreeth Achar, Srinivasa G. Narasimhan
2014 Lecture Notes in Computer Science  
Illumination defocus and global illumination effects are major challenges for active illumination scene recovery algorithms. Illumination defocus limits the working volume of projector-camera systems and global illumination can induce large errors in shape estimates. In this paper, we develop an algorithm for scene recovery in the presence of both defocus and global light transport effects such as interreflections and sub-surface scattering. Our method extends the working volume by using
more » ... red light patterns at multiple projector focus settings. A careful characterization of projector blur allows us to decode even partially out-of-focus patterns. This enables our algorithm to recover scene shape and the direct and global illumination components over a large depth of field while still using a relatively small number of images (typically 25-30). We demonstrate the effectiveness of our approach by recovering high quality depth maps of scenes containing objects made of optically challenging materials such as wax, marble, soap, colored glass and translucent plastic.
doi:10.1007/978-3-319-10590-1_14 fatcat:yhaem2widrc6xcfguzyjdmscsi

Compensating for Motion during Direct-Global Separation

Supreeth Achar, Stephen T. Nuske, Srinivasa G. Narasimhan
2013 2013 IEEE International Conference on Computer Vision  
Separating the direct and global components of radiance can aid shape recovery algorithms and can provide useful information about materials in a scene. Practical methods for finding the direct and global components use multiple images captured under varying illumination patterns and require the scene, light source and camera to remain stationary during the image acquisition process. In this paper, we develop a motion compensation method that relaxes this condition and allows direct-global
more » ... ation to be performed on video sequences of dynamic scenes captured by moving projector-camera systems. Key to our method is being able to register frames in a video sequence to each other in the presence of time varying, high frequency active illumination patterns. We compare our motion compensated method to alternatives such as single shot separation and frame interleaving as well as ground truth. We present results on challenging video sequences that include various types of motions and deformations in scenes that contain complex materials like fabric, skin, leaves and wax.
doi:10.1109/iccv.2013.187 dblp:conf/iccv/AcharNN13 fatcat:7jpxx6ktojeppppnbiwlcrwsti

Epipolar time-of-flight imaging

Supreeth Achar, Joseph R. Bartels, William L. 'Red' Whittaker, Kiriakos N. Kutulakos, Srinivasa G. Narasimhan
2017 ACM Transactions on Graphics  
doi:10.1145/3072959.3073686 fatcat:kk3nfov7wncgvhauikprdukiz4

Large scale visual localization in urban environments

Supreeth Achar, C.V. Jawahar, K Madhava Krishna
2011 2011 IEEE International Conference on Robotics and Automation  
Supreeth Achar is currently a graduate student at RI CMU; C.V. Jawahar is with  ... 
doi:10.1109/icra.2011.5979925 dblp:conf/icra/AcharJK11 fatcat:7qfqvl4uyvb53g253wkdtrt54u

Adaptation and Learning for Image Based Navigation

Supreeth Achar, C.V. Jawahar
2008 2008 Sixth Indian Conference on Computer Vision, Graphics & Image Processing  
Image based methods are a new approach for solving problems in mobile robotics. Instead of building a metric (3D) model of the environment, these methods work directly in the sensor (image) space. The environment is represented as a topological graph in which each node contains an image taken at some pose in the workspace, and edges connect poses between which a simple path exists. This type of representation is highly scalable and is also well suited to handle the data association problems
more » ... effect metric model based methods. In this paper, we present an efficient, adaptive method for qualitative localization using content based image retrieval techniques. In addition, we demonstrate an algorithm which can convert this topological graph into a metric model of the environment by incorporating information about loop closures.
doi:10.1109/icvgip.2008.72 dblp:conf/icvgip/AcharJ08 fatcat:bpbh6536dfbjhlb4asogkiwztu

Self-supervised segmentation of river scenes

Supreeth Achar, Bharath Sankaran, Stephen Nuske, Sebastian Scherer, Sanjiv Singh
2011 2011 IEEE International Conference on Robotics and Automation  
Achar, S. Nuske, S. Scherer and S. Singh are with The Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15232, U.S.A., {supreeth,nuske,basti,ssingh} B.  ... 
doi:10.1109/icra.2011.5980157 dblp:conf/icra/AcharSNSS11 fatcat:twdyi45z4vdkfpoh43jcwpwpe4

Visual servoing based on Gaussian mixture models

A.H. Abdul Hafez, Supreeth Achar, C.V. Jawahar
2008 2008 IEEE International Conference on Robotics and Automation  
,supreeth@students.} 2. Tracking step in some of the recent algorithm is integrated with the control law.  ... 
doi:10.1109/robot.2008.4543702 dblp:conf/icra/HafezAJ08 fatcat:sl2uahveebd6hb36x3piahuewu

Homogeneous codes for energy-efficient illumination and imaging

Matthew O'Toole, Supreeth Achar, Srinivasa G. Narasimhan, Kiriakos N. Kutulakos
2015 ACM Transactions on Graphics  
The homogeneous factorization equation maximizes energy efficiency subject to all imaging constraints, by maximizing the scalar γ or, equivalently, minimizing its reciprocal γ −1 : min γ,t,M,L
doi:10.1145/2766897 fatcat:2odc2wskjzcafg72ttxpxxmjpm

Autonomous image-based exploration for mobile robot navigation

D. Santosh, Supreeth Achar, C. V. Jawahar
2008 2008 IEEE International Conference on Robotics and Automation  
D Santosh*, Supreeth Achar, C V Jawahar Abstract-Image-based navigation paradigms have recently emerged as an interesting alternative to conventional modelbased methods in mobile robotics.  ...  environment is generally represented as a topological graph in which each node represents a position in the workspace and stores the sensor readings (i.e., images from the camera) observed at D Santosh, S Achar  ... 
doi:10.1109/robot.2008.4543622 dblp:conf/icra/SantoshAJ08 fatcat:ehfye67n5vccrf2hai3hoj4s3a

Yield estimation in vineyards by visual grape detection

Stephen Nuske, Supreeth Achar, Terry Bates, Srinivasa Narasimhan, Sanjiv Singh
2011 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems  
Stephen Nuske, Supreeth Achar, Srinivasa Narasimhan and Sanjiv Singh at Robotics Institute, Carnegie Mellon University, Pittsburgh, PA, USA, 15213 Terry Bates at Cornell University, 6592  ... 
doi:10.1109/iros.2011.6095069 dblp:conf/iros/NuskeABNS11 fatcat:jhv4lc4sknd6tdirhjaaniflx4

River mapping from a flying robot: state estimation, river detection, and obstacle mapping

Sebastian Scherer, Joern Rehder, Supreeth Achar, Hugh Cover, Andrew Chambers, Stephen Nuske, Sanjiv Singh
2012 Autonomous Robots  
Exploration from a flying vehicle is attractive because it extends the sensing Sebastian Scherer, Supreeth Achar, Hugh Cover, Andrew Chambers, Stephen Nuske, Sanjiv Singh are with the Robotics Institute  ...  Details of our feature evaluation experiments can be found in Achar et al (2011) .  ... 
doi:10.1007/s10514-012-9293-0 fatcat:nkv74xudhzbm5j2wsiykm3k6ke

Perception for a river mapping robot

Andrew Chambers, Supreeth Achar, Stephen Nuske, Jorn Rehder, Bernd Kitt, Lyle Chamberlain, Justin Haines, Sebastian Scherer, Sanjiv Singh
2011 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems  
Rivers with heavy vegetation are hard to map from the air. Here we consider the task of mapping their course and the vegetation along the shores with the specific intent of determining river width and canopy height. A complication in such riverine environments is that only intermittent GPS may be available depending on the thickness of the surrounding canopy. We present a multimodal perception system to be used for the active exploration and mapping of a river from a small rotorcraft flying a
more » ... w meters above the water. We describe three key components that use computer vision, laser scanning, and inertial sensing to follow the river without the use of a prior map, estimate motion of the rotorcraft, ensure collisionfree operation, and create a three dimensional representation of the riverine environment. While the ability to fly simplifies the navigation problem, it also introduces an additional set of constraints in terms of size, weight and power. Hence, our solutions are cognizant of the need to perform multi-kilometer missions with a small payload. We present experimental results along a 2km loop of river using a surrogate system.
doi:10.1109/iros.2011.6095040 dblp:conf/iros/ChambersANRKCHSS11 fatcat:rncd337d6za5vjihyerwoxx6ae

A Dark Flash Normal Camera [article]

Zhihao Xia, Jason Lawrence, Supreeth Achar
Casual photography is often performed in uncontrolled lighting that can result in low quality images and degrade the performance of downstream processing. We consider the problem of estimating surface normal and reflectance maps of scenes depicting people despite these conditions by supplementing the available visible illumination with a single near infrared (NIR) light source and camera, a so-called "dark flash image". Our method takes as input a single color image captured under arbitrary
more » ... ble lighting and a single dark flash image captured under controlled front-lit NIR lighting at the same viewpoint, and computes a normal map, a diffuse albedo map, and a specular intensity map of the scene. Since ground truth normal and reflectance maps of faces are difficult to capture, we propose a novel training technique that combines information from two readily available and complementary sources: a stereo depth signal and photometric shading cues. We evaluate our method over a range of subjects and lighting conditions and describe two applications: optimizing stereo geometry and filling the shadows in an image.
doi:10.48550/arxiv.2012.06125 fatcat:kxpwvitq4vbijjyrzggnjnrsfe

Visual Yield Estimation in Vineyards: Experiments with Different Varietals and Calibration Procedures

Stephen Nuske, Supreeth Achar, Kamal Gupta, Srinivasa G. Narasimhan, Sanjiv Singh
A crucial practice for vineyard managers is to control the amount of fruit hanging on their vines to reach yield and quality goals. Current vine manipulation methods to adjust level of fruit are inaccurate and ineffective because they are often not performed according to quantitative yield information. Even when yield predictions are available they are inaccurate and spatially coarse because the traditional measurement practice is to use labor intensive, destructive, hand measurements that are
more » ... oo sparse to adequately measure spatial variation in yield. We present an approach to predict the vineyard yield automatically and non-destructively with cameras. The approach uses camera images of the vines collected from farm vehicles driving along the vineyard rows. Computer vision algorithms are applied to the images to detect and count the grape berries. Shape and texture cues are used to detect berries even when they are of similar color to the vine leaves. Images are automatically registered together and the vehicle position along the row is tracked to generate high resolution yield predictions. Results are presented from four different vineyards, including wine and table-grape varieties. The harvest yield was collected from 948 individual vines, totaling approximately 2.5km of vines, and used to validate the predictions we generate automatically from the camera images. We present different calibration approaches to convert our image berry count to harvest yield and find that we can predict yield of individual vineyard rows to within 10\% and overall yield to within 5% of the actual harvest weight.
doi:10.1184/r1/6561593 fatcat:ufjmbnqz25dnjjd2y4rwhpg3x4

Visual localization in highly crowded urban environments

A. H. Abdul Hafez, Manpreet Singh, K. Madhava Krishna, C. V. Jawahar
2013 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems  
The authors would like to thank Aayush Bansal and Supreeth Achar for their valuable inputs and insights.  ...  Achar et al. [10] investigated the problem of localization in urban environments.  ... 
doi:10.1109/iros.2013.6696749 dblp:conf/iros/HafezSKJ13 fatcat:3im46xp6iveybandu7b6326lre
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