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Since its inception in 1998, ICVGIP has provided a forum to researchers in image processing, computer vision, graphics and related areas. The conference has grown in strength over the years and established itself as a flagship conference in computer vision.
Reinforced random forest
Reinforcement learning improves classification accuracy. But use of reinforcement learning is relatively unexplored in case of random forest classifier. We propose a reinforced random forest (RRF) classifier that exploits reinforcement learning to ...
Prototypes based discriminative appearance model for object tracking
Occlusion is one of the major challenges for object tracking in real life scenario. Various techniques in particle filter framework have been developed to solve this problem. This framework depends on two issues: motion model and observation (likelihood)...
Adaptive artistic stylization of images
In this work, we present a novel non-photorealistic rendering method which produces good quality stylization results for color images. The procedure is driven by saliency measure in the foreground and the background region. We start with generating ...
Improving person re-identification systems: a novel score fusion framework for rank-n recognition
Person re-identification is an essential technique for video surveillance applications. Most existing algorithms for person re-identification deal with feature extraction, metric learning or a combination of both. Combining successful state-of-the-art ...
An image analysis approach for transcription of music played on keyboard-like instruments
Music transcription refers to the process of analyzing a piece of music to generate a sequence of constituent notes and their duration. Transcription of music from audio signals is fraught with problems due to auditory interference such as ambient noise,...
Deep automatic license plate recognition system
Automatic License Plate Recognition (ALPR) has important applications in traffic surveillance. It is a challenging problem especially in countries like in India where the license plates have varying sizes, number of lines, fonts etc. The difficulty is ...
How much can a Gaussian smoother denoise?
Recently, a suite of increasingly sophisticated methods have been developed to suppress additive noise from images. Most of these methods take advantage of sparsity of the underlying signal in a specific transform domain to achieve good visual or ...
Generic TV advertisement detection using progressively balanced perceptron trees
Automatic detection of TV advertisements is of paramount importance for various media monitoring agencies. Existing works in this domain have mostly focused on news channels using news specific features. Most commercial products use near copy detection ...
Supervised deep segmentation network for brain extraction
Recent past has seen an inexorable shift towards the use of deep learning techniques to solve a myriad of problems in the field of medical imaging. In this paper, a novel segmentation method involving a fully-connected deep neural network called Deep ...
Robust registration of Mouse brain slices with severe histological artifacts
Brain mapping research is facilitated by first aligning digital images of mouse brain slices to standardized atlas framework such as the Allen Reference Atlas (ARA). However, conventional processing of these brain slices introduces many histological ...
Image defencing via signal demixing
We present a novel algorithm to remove near regular, fence or wire like foreground patterns from an image. The fence detection or fence removal algorithms, developed so far, have poor performance in detecting the fence. We use signal demixing to utilize ...
Don't see me, just filter me: towards secure cloud based filtering using Shamir's secret sharing and POB number system
Cloud computing paradigm is attracting individuals as well as organizations all round the globe due to its multiple facilities of powerful resources, storage hubs, computational power and cost effective solutions. However, distributed cloud data centers ...
Hierarchical structured learning for indoor autonomous navigation of Quadcopter
Autonomous navigation of generic monocular quadcopter in the indoor environment requires sophisticated approaches for perception, planning and control. This paper presents a system which enables a miniature quadcopter with a frontal monocular camera to ...
Event recognition in broadcast soccer videos
Automatic recognition of important events in soccer broadcast videos plays a vital role in many applications including video summarization, indexing, content-based search, and in performance analysis of players and teams. This paper proposes an approach ...
A fast identity-independent expression recognition system for robust cartoonification using smart devices
Facial expressions convey rich information about emotions, intentions and other internal states of a person. Automatic facial expression and cartoonification systems are aiming towards the application of computer vision systems in human computer ...
Automatic detection of Malaria infected RBCs from a focus stack of bright field microscope slide images
Malaria is a deadly infectious disease affecting red blood cells in humans due to the protozoan of type Plasmodium. In 2015, there is an estimated death toll of 438, 000 patients out of the total 214 million malaria cases reported world-wide. Thus, ...
MPMF: multi-part multi-feature based object tracking
The objective of tracking is to determine the states of an object in video frames while maintaining appearance and motion consistency. In this paper, we propose a novel multi-part multi-feature (MPMF) based object tracking which falls in the category of ...
Automated brain tractography segmentation using curvature points
Classification of brain fiber tracts is an important problem in brain tractography analysis. We propose a supervised algorithm which learns features for anatomically meaningful fiber clusters, from labeled DTI white matter data. The classification is ...
Depth estimation from single image using machine learning techniques
In this paper, the problem of depth estimation from single monocular image is considered. The depth cues such as motion, stereo correspondences are not present in single image which makes the task more challenging. We propose a machine learning based ...
Deep neural networks for segmentation of basal ganglia sub-structures in brain MR images
Automated segmentation of brain structure in magnetic resonance imaging (MRI) scans is an important first step in diagnosis of many neurological diseases. In this paper, we focus on segmentation of the constituent sub-structures of basal ganglia (BG) ...
Crowd motion analysis for group detection
Understanding crowd dynamics is an interesting problem in computer vision owing to its various applications. We propose a dynamical system to model the dynamics of collective motion of the crowd. The model learns the spatio-temporal interaction pattern ...
Voxel-based morphometry and minimum redundancy maximum relevance method for classification of Parkinson's disease and controls from T1-weighted MRI
- Bharti Rana,
- Akanksha Juneja,
- Mohit Saxena,
- Sunita Gudwani,
- S Senthil Kumaran,
- R K Agrawal,
- Madhuri Behari
Parkinson's disease (PD) is a neurodegenerative disorder, which needs to be accurately diagnosed in early stage. Voxel-based morphometry (VBM) has been extensively utilized to determine focal changes between PD patients and controls. However, it is not ...
Document blur detection using edge profile mining
We present an algorithm for automatic blur detection of document images using a novel approach based on edge intensity profiles. Our main insight is that the edge profiles are a strong indicator of the blur present in the image, with steep profiles ...
Event geo-localization and tracking from crowd-sourced video metadata
We propose a novel technique for event geo-localization (i.e. 2-D location of the event on the surface of the earth) from the sensor metadata of crowd-sourced videos collected from smartphone devices. With the help of sensors available in the smartphone ...
Local dominant binary patterns for recognition of multi-view facial expressions
In this paper, a novel framework is proposed for automatic recognition of facial expressions. However, the face images for the proposed problem are captured at multiple view angle (i.e., multi-view facial expressions). The proposed scheme introduces a ...
Color restoration in turbid medium
Light scattering and color distortions are two major issues with underwater imaging. Scattering occurs due to turbidity of the medium and color distortions are caused by differential attenuation of wavelengths as a function of depth. As a result, ...
First quantization matrix estimation for double compressed JPEG images utilizing novel DCT histogram selection strategy
The Double JPEG problem in image forensics has been gaining importance since it involves two compression cycles and there is a possibility of tampering having taken place after the first cycle thereby calling for accurate methods to detect and localize ...
Classification of Schizophrenia versus normal subjects using deep learning
Motivated by deep learning approaches to classify normal and neuro-diseased subjects in functional Magnetic Resonance Imaging (fMRI), we propose stacked autoencoder (SAE) based 2-stage architecture for disease diagnosis. In the proposed architecture, a ...
A framework to assess Sun salutation videos
There are many exercises which are repetitive in nature and are required to be done with perfection to derive maximum benefits. Sun Salutation or Surya Namaskar is one of the oldest yoga practice known. It is a sequence of ten actions or 'asanas' where ...
Image hallucination at different times of day using locally affine model and kNN template matching from time-lapse images
Image Hallucination has many applications in areas such as image processing, computational photography and image fusion. In this paper, we present an image Hallucination technique based on the template (patch) matching from the database of time lapse ...
Index Terms
- Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing
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Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
ICVGIP '16 | 286 | 95 | 33% |
Overall | 286 | 95 | 33% |