24 research outputs found
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3D Reconstruction Using Lidar and Visual Images
In this research, multi-perspective image registration using LiDAR and visual images was considered. 2D-3D image registration is a difficult task because it requires the extraction of different semantic features from each modality. This problem is solved in three parts. The first step involves detection and extraction of common features from each of the data sets. The second step consists of associating the common features between two different modalities. Traditional methods use lines or orthogonal corners as common features. The third step consists of building the projection matrix. Many existing methods use global positing system (GPS) or inertial navigation system (INS) for an initial estimate of the camera pose. However, the approach discussed herein does not use GPS, INS, or any such devices for initial estimate; hence the model can be used in places like the lunar surface or Mars where GPS or INS are not available. A variation of the method is also described, which does not require strong features from both images but rather uses intensity gradients in the image. This can be useful when one image does not have strong features (such as lines) or there are too many extraneous features
Study of Computational Image Matching Techniques: Improving Our View of Biomedical Image Data
Image matching techniques are proven to be necessary in various fields of science and engineering, with many new methods and applications introduced over the years. In this PhD thesis, several computational image matching methods are introduced and investigated for improving the analysis of various biomedical image data. These improvements include the use of matching techniques for enhancing visualization of cross-sectional imaging modalities such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), denoising of retinal Optical Coherence Tomography (OCT), and high quality 3D reconstruction of surfaces from Scanning Electron Microscope (SEM) images. This work greatly improves the process of data interpretation of image data with far reaching consequences for basic sciences research. The thesis starts with a general notion of the problem of image matching followed by an overview of the topics covered in the thesis. This is followed by introduction and investigation of several applications of image matching/registration in biomdecial image processing: a) registration-based slice interpolation, b) fast mesh-based deformable image registration and c) use of simultaneous rigid registration and Robust Principal Component Analysis (RPCA) for speckle noise reduction of retinal OCT images. Moving towards a different notion of image matching/correspondence, the problem of view synthesis and 3D reconstruction, with a focus on 3D reconstruction of microscopic samples from 2D images captured by SEM, is considered next. Starting from sparse feature-based matching techniques, an extensive analysis is provided for using several well-known feature detector/descriptor techniques, namely ORB, BRIEF, SURF and SIFT, for the problem of multi-view 3D reconstruction. This chapter contains qualitative and quantitative comparisons in order to reveal the shortcomings of the sparse feature-based techniques. This is followed by introduction of a novel framework using sparse-dense matching/correspondence for high quality 3D reconstruction of SEM images. As will be shown, the proposed framework results in better reconstructions when compared with state-of-the-art sparse-feature based techniques. Even though the proposed framework produces satisfactory results, there is room for improvements. These improvements become more necessary when dealing with higher complexity microscopic samples imaged by SEM as well as in cases with large displacements between corresponding points in micrographs. Therefore, based on the proposed framework, a new approach is proposed for high quality 3D reconstruction of microscopic samples. While in case of having simpler microscopic samples the performance of the two proposed techniques are comparable, the new technique results in more truthful reconstruction of highly complex samples. The thesis is concluded with an overview of the thesis and also pointers regarding future directions of the research using both multi-view and photometric techniques for 3D reconstruction of SEM images
Scene Monitoring With A Forest Of Cooperative Sensors
In this dissertation, we present vision based scene interpretation methods for monitoring of people and vehicles, in real-time, within a busy environment using a forest of co-operative electro-optical (EO) sensors. We have developed novel video understanding algorithms with learning capability, to detect and categorize people and vehicles, track them with in a camera and hand-off this information across multiple networked cameras for multi-camera tracking. The ability to learn prevents the need for extensive manual intervention, site models and camera calibration, and provides adaptability to changing environmental conditions. For object detection and categorization in the video stream, a two step detection procedure is used. First, regions of interest are determined using a novel hierarchical background subtraction algorithm that uses color and gradient information for interest region detection. Second, objects are located and classified from within these regions using a weakly supervised learning mechanism based on co-training that employs motion and appearance features. The main contribution of this approach is that it is an online procedure in which separate views (features) of the data are used for co-training, while the combined view (all features) is used to make classification decisions in a single boosted framework. The advantage of this approach is that it requires only a few initial training samples and can automatically adjust its parameters online to improve the detection and classification performance. Once objects are detected and classified they are tracked in individual cameras. Single camera tracking is performed using a voting based approach that utilizes color and shape cues to establish correspondence in individual cameras. The tracker has the capability to handle multiple occluded objects. Next, the objects are tracked across a forest of cameras with non-overlapping views. This is a hard problem because of two reasons. First, the observations of an object are often widely separated in time and space when viewed from non-overlapping cameras. Secondly, the appearance of an object in one camera view might be very different from its appearance in another camera view due to the differences in illumination, pose and camera properties. To deal with the first problem, the system learns the inter-camera relationships to constrain track correspondences. These relationships are learned in the form of multivariate probability density of space-time variables (object entry and exit locations, velocities, and inter-camera transition times) using Parzen windows. To handle the appearance change of an object as it moves from one camera to another, we show that all color transfer functions from a given camera to another camera lie in a low dimensional subspace. The tracking algorithm learns this subspace by using probabilistic principal component analysis and uses it for appearance matching. The proposed system learns the camera topology and subspace of inter-camera color transfer functions during a training phase. Once the training is complete, correspondences are assigned using the maximum a posteriori (MAP) estimation framework using both the location and appearance cues. Extensive experiments and deployment of this system in realistic scenarios has demonstrated the robustness of the proposed methods. The proposed system was able to detect and classify targets, and seamlessly tracked them across multiple cameras. It also generated a summary in terms of key frames and textual description of trajectories to a monitoring officer for final analysis and response decision. This level of interpretation was the goal of our research effort, and we believe that it is a significant step forward in the development of intelligent systems that can deal with the complexities of real world scenarios
Mobile Robots
The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations
Annual Report 2018-19
Not AvailableA large number of germplasm accessions of
horticultural crops are being conserved and
maintained in the field gene banks. Among fruit
crops, a total of 1110,190,759 and 54 viable
germplasm are being conserved at main station
ICAR-IIHR, CHES, Bhubaneswar, Chettalli and
Hirehalli, respectively. Whereas in vegetable crops,
a total of 5694 and 842 viable germplasm are being
conserved at main station and at CHES
Bhubaneswar, respectively, including leafy and
other underutilized vegetables.
A total of 459 germplasm in flower crops and 225 in
medicinal crops and 33 accessions of mushroom are
also conserved at ICAR-IIHR, Bengaluru. ICARIIHR has been identified as the National Repository
for Rose by PPV&FRA, under which the digital
rose repository of 75 rose varieties have been built
for easy identification, grouping and selection of
varieties.
The germplasm collected and conserved has also
been characterized using Bioversity International or
NBPGR descriptors. In fruit crops, characters of 17
Appemidi and 26 mango accessions were
morphologically characterized and fruit parameters
of 25 accessions from FGB were characterized
based on Bioversity International descriptors. Nine
USDA germplasm of pomegranate were
characterized for vegetative and fruit traits. Two
varieties of guava, two exotic varieties of papaya,
and three custard apple varieties were characterized
for fruit traits as per the DUS descriptor. Three
g e r m p l a s m o f p i n e a p p l e h a v e b e e n
morphologically characterized and evaluated for
yield and quality.
In vegetable crops, 5 in chilli, 54 in brinjal, 45 in
radish, 5 in onion were characterized using NBPGR
descriptors. A total of 1000 accessions were
evaluated for 24 characters based on NBPGR
descriptors for growth, yield and quality. A total of
42 cylindrical and 18 round types of bottle gourd
were evaluated for resistance to powdery mildew.
Forty-six accessions comprising 15 summer squash
and 26 butternut types were characterized for 14
quantitative and 11 qualitative traits based on
NBPGR descriptors. Eighty six drumstick
germplasm along with released varieties were
evaluated for leaf nutritional parametersNot Availabl
Perspectives for a National GI Policy (Including a National GI Policy Draft) (NIAS Report No. R11-2012)
GI (Geographic Inf ormation) …..
…..refers to any information that has a geographical
or location context. The GI includes satellite images,
aerial images/data, maps – topographic and
thematic, ground survey data, positioning data,
geo-tagged attributes/tables etc and also the derivatives
from their processing – all of which are
amenable to visual display, integration and processing
and serving as maps/images in the spatial
domain.
Policy……
is declared objectives that a government seeks to
achieve and preserve in national interest ….
…… typically a “Statement of Inten
Telemedicine
Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios