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In this paper, we proposed a segmentation approach that not only segment an interest object but also label different semantic parts of the object, where a discriminative model is presented to describe an object in real world images as multiply, disparate and correlative parts. We propose a multi-stage segmentation approach to make inference on the segments of an object. Then we train it under the...
In this paper, we present, first, a new method for color feature extraction based on SURF detectors. Then, we proved its efficiency for flower image classification. Therefore, we described visual content of the flower images using compact and accurate descriptors. These features are combined and the learning process is performed using a multiple kernel framework with a SVM classifier. The proposed...
Face indexing is a very popular research topic and it has been investigated over the last 10 years. It can be used for a wide range of applications such as automatic video content analysis, data mining, video annotation and labeling, etc. In this work a fully automated framework that can detect how many people are present in a generic video (even having low resolution and/or taken from a mobile camera)...
We propose a method for estimating the degree of a driver's drowsiness on the basis of changes in facial expressions captured by an IR camera. Typically, drowsiness is accompanied by drooping eyelids. Therefore, most related studies have focused on tracking eyelid movement by monitoring facial feature points. However, the drowsiness feature emerges not only in eyelid movements but also in other facial...
We propose a robust real-time person detection system, which aims to serve as solid foundation for developing solutions at an elevated level of reliability. Our belief is that clever handling of input data correlated with efficacious training algorithms are key for obtaining top performance. We introduce a comprehensive training method based on random sampling that compiles optimal classifiers with...
Pairwise and higher order potentials in the Hierarchical Conditional Random Field (HCRF) model play a vital role in smoothing region boundary and extracting actual object contour in the labeling space. However, pairwise potential evaluated by color information has the tendency to over-smooth small regions which are similar to their neighbors in the color space; and the higher order potential associated...
Starting with a selective retrospective of the history of software visualization, I will identify various trends and paradigms of previous and current research. In particular, I will discuss examples of applying visualization techniques to analyze the past and present state of software as well as to predict its future development. I will argue that prediction is an important task, but that software...
Recent research has established the negative impact of facial cosmetics on the matching accuracy of automated face recognition systems. In this paper, we analyze the impact of cosmetics on automated gender and age estimation algorithms. In this regard, we consider the use of facial cosmetics for (a) gender spoofing where male subjects attempt to look like females and vice versa, and (b) age alteration...
The gesture recognition using motion capture data and depth sensors has recently drawn more attention in vision recognition. Currently most systems only classify dataset with a couple of dozens different actions. Moreover, feature extraction from the data is often computational complex. In this paper, we propose a novel system to recognize the actions from skeleton data with simple, but effective,...
We present a technique for locating landmarks in images of human faces. We replace the 1D gradient profiles of the classical Active Shape Model (ASM) (Cootes and Taylor, 1993) with a simplified form of SIFT descriptors (Lowe, 2004), and use Multivariate Adaptive Regression Splines (MARS) (Friedman, 1991) for descriptor matching. This modified ASM is fast and performs well against existing techniques...
The Spatial Pyramid Matching approach has become very popular to model images as sets of local bag-of-words. The image comparison is then done region-by-region with an intersection kernel. Despite its success, this model presents some limitations: the grid partitioning is predefined and identical for all images and the matching is sensitive to intra- and inter-class variations. In this paper, we propose...
This paper presents a novel and unsupervised approach for discovering “sudden” movements in video surveillance videos. The proposed approach automatically detects quick motions in a video, corresponding to any action. A set of possible actions is not required and the proposed method successfully detects potentially alarm-raising actions without training or camera calibration. Moreover, the system...
This paper introduces VabCut, a video extension of GrabCut, an original unsupervised solution to tackle the video foreground object segmentation task. Vabcut works on an extension of the RGB colour domain to RGBM, where M is the motion. It requires a prior step: the computation of the motion layer (M-layer) of the frame to segment. In order to compute this layer we propose to intersect the frame to...
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