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This paper exploits the problem of fitting special forms of annuli that correspond to 4-connected digital circles to a given set of points in 2D images in the presence of noise by maximizing the number of inliers, namely the consensus set. We prove that the optimal solutions can be described by solutions with three points on the annulus boundary. These solutions correspond to vertices of the preimage...
Basic understanding and recognition of human actions can be accomplished by modeling the spatiotemporal relationship among major skeletal joints. In this work we present an approach that models human actions using temporal causal relations of joint movements. The relations form a graph with joints as nodes and edges induced by the Granger causality measure between pairs of joint point processes. Each...
We introduce a novel subspace segmentation method called Minimal Squared Frobenius Norm Representation (MSFNR). MSFNR performs data clustering by solving a convex optimization problem. We theoretically prove that in the noiseless case, MSFNR is equivalent to the classical Factorization approach and always classifies data correctly. In the noisy case, we show that on both synthetic and real-word datasets,...
Detecting and identifying Regions of Interest (ROIs) is an important task for navigation and retrieval services. In this paper, we focus on indoor scene images and detect object regions such as shop signs and merchandise. Our method is based on two approaches; 1) Indoor structure analysis from a single image by learning the types of scenes. 2) Detect ROIs by taking advantage of the relationship of...
This paper delves into the effectiveness of a gait recognition process depending on the length of the video sequence used. To this end, a well-known gait representation, the Gait Energy Image (GEI), is incrementally computed from gait cycles in the order they occur. The main objective is to assess the problem of the minimum number of gait cycles required to obtain discriminant GEIs. An experimental...
Reconstruction and repairing of missing parts or scratches of digital historical images is an important trend which has been extensively used in artwork restoration. Image completion is an active subject in image and video processing, which deals with the recovery of original data. Most previous image completion techniques consume more time in extensive search to find the best texture to repair the...
Labeling connected components and calculating the Euler number, connected-component number, and hole number in a binary image are usually necessary for image analysis, pattern recognition, and computer (robot) vision. This paper presents a new algorithm for calculating the Euler number, connected-component number, and hole number in a binary image by labeling connected components in the binary image...
This paper addresses the task of predicting the battery capacity degradation ratio for a given usage pattern. This is an interesting pattern recognition task, where each usage pattern is represented as a trajectory in a feature space, and the prediction model captures the previous usage trajectory patterns. The main technical challenge here is how to build a good model from a limited number of training...
In this paper, we further develop the research on recognition of activities, in videos recorded with wearable cameras, with Hierarchical Hidden Markov Model classifiers. The visual scenes being of a strong complexity in terms of motion and visual content, good performances have been obtained using multiple visual and audio cues. The adequate fusion of features from physically different description...
In the dissimilarity representation approach, objects are represented by their dissimilarities with respect to a representation set, rather than by features. Up to now, the representation or prototype set has usually been selected from the training data, limiting the different aspects that can be captured, especially when the training data set is small. This paper studies the performance change if...
During the image placement onto the compositing surface (mosaic), stitching algorithms try to minimize visual inconsistencies (texture discontinuities), seam induced color gradients, and blurry image regions. These problems are classically processed separately. In this contribution, we describe a two step graph-cut algorithm that combines these issues. In the first step, optimal seam locations are...
In this paper, we propose a new descriptor which is computed by comparing invariant cross color channels of pairs of points in the local patch. To efficiently obtain the sampled pairs of points, a galaxy sampling pattern is proposed. As shown in the experiments, our descriptor using invariant cross color channels and the galaxy sampling can achieve the best performance in most cases with slight computation...
Navigating safely in outdoor environments is a challenging activity for vision-impaired people. This paper is a step towards developing an assistive navigation system for the blind. We propose a robust method for detecting the pedestrian marked lanes at traffic junctions. The proposed method includes two stages: regions of interest (ROI) extraction and lane marker verification. The ROI extraction...
This paper presents the different steps for an automatic fluorescence-labelled cell classification method. First a data features study is discussed in order to describe cell texture by means of morphological and statistical texture descriptors. Then, results on supervised classification using logistic regression, random forest and neural networks, for both morphological and statistical descriptors,...
Recently the improved bag of features (BoF) model with locality-constrained linear coding (LLC) and spatial pyramid matching (SPM) achieved state-of-the-art performance in image classification. However, only adopting SPM to exploit spatial information is not enough for satisfactory performance. In this paper, we use hierarchical temporal memory (HTM) cortical learning algorithms to extend this LLC...
It is suggested how a Markov random field can be used for object tracking with context information. The tracking is formulated as a two layer process. In the first phase, the image is represented by a set of feature points which are tracked by a standard tracker. In the second phase, the proposed semi-supervised learning and labeling algorithm is used to label the points to three classes — object,...
By segmenting moving objects out and then densely stitching them into background frames, video synopsis provides an efficient way to condense long videos while preserving most activities. Existing video synopsis methods, however, often suffer from either high computation cost due to global energy minimization or unsatisfactory condense rate to avoid loss of important object activities. To address...
Zernike moments are commonly used in pattern recognition but are not suited for texture analysis. In this paper we introduce regional Zernike moments (RZM) where we combine the Zernike moments for the pixels in a region to create a measure suitable for texture analysis. We compare our proposed measures to texture measures based on Gabor filters, Haralick cooccurrence matrices and local binary patterns...
2D Gel Electrophoresis image analysis is widely recognized as one of the most crucial processes following a proteomic experiment. Amongst its stages, detection and segmentation are the most challenging ones. The available software packages and techniques fail to detect and segment some of the real spots while they often detect a vast number of spurious spots. In this paper, an original approach to...
While the skeleton of a 2D shape corresponds to a planar graph, its encoding by usual graph data structures does not allow to capture its planar properties. Graph kernels may be defined on graph's encoding of the skeleton in order to define a similarity measure between shapes. Such graph kernels are usually based on a decomposition of graphs into bags of walks or trails. These linear patterns do not...
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