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This paper proposes a simple yet novel method for recognition of certain sorts of moving entities incorporating their shape and motion patterns. Although shape features have been commonly employed in object recognition, motion characteristics are in general not integrated to geometric models. In the interest of utilizing the motion attributes, the trajectories are investigated to extract the ‘coherence...
The philosophy of user-friendly and awareness of green environmental protection currently are the important design concept of industrial design. There are not only similarities and intersection, but also contradictions and conflicts. This article focuses on how to coordinate the relationship between user-friendly design and awareness of green environmental protection, how to create an optimal balance...
We propose a bilateral symmetry Gabor Wavelet Network (BSGWN) for face modeling and online tracking. Bilateral symmetry wavelet pairs reduce the computational complexity of the BSGWN optimization and yield robust tracking performance in real world environments. We decompose face image into a set of frequency components. The face model of Gabor wavelets is built on the reconstructed image from corresponding...
This paper presents a new fully automatic method for segmenting upright people in the images. Is is based on the efficient graph cut segmentation. Since colour and texture prevent from discriminating this particular class, silhouette shape is used instead. The graph cut is guided by a non-binary template of silhouette that represents the probability of each pixel to be a part of the person to segment...
In this paper a new approach is proposed to enhance images that inspired by adaptive global and local processing of the human visual system. The method first uses a principal component analysis to the original image to provide orthogonality between channels and thus reduces the chromatic changes induced by the processing of luminance. Then a nonlinear method is applied to adjust the global dynamic...
This paper describes a human shape reconstruction method from multiple cameras in daily living environment, which leads to robust markerless motion capture. Due to continual illumination changes in daily space, it had been difficult to get human shape by background subtraction methods. Recent statistical foreground segmentation techniques based on graph-cuts, which combine background subtraction information...
In this paper, we compare the behavior of four viable dense stereo correspondence measures, which are Normalized Cross-Correlation (NCC), Histograms of Oriented Gradients (HOG), Mutual Information (MI), and Local Self-Similarity (LSS), for thermal-visible human monitoring. Our comparison is based on a Winner Take All (WTA) box matching stereo method. We evaluate the accuracy and the discriminative...
When using the human mind as a template for artificial intelligence systems, principles of human thinking have to be modeled. One such very important principle is defense. Hence, in this article we describe a formalism to implement psychoanalytic defense mechanisms in artificial intelligence systems. They can be seen as transformations. A tuple1 consisting of perceptions or drives (of a software agent...
This paper presents a multi-modal affect recognition system that is capable of effectively estimating human affective states through analyzing and fusing a number of non-invasive external cues. The proposed system consists of a probabilistic information fusion model based on the influence diagram and a set of data analysis, feature extraction and affect recognition modules for processing heterogeneous...
Seabird populations are considered an important and accessible indicator of the health of marine environments: variations have been linked with climate change and pollution [1]. However, manual monitoring of large populations is labour-intensive, and requires significant investment of time and effort. In this paper, we propose a novel detection system for monitoring a specific population of Common...
This paper proposes a human detection method using variational mean field approximation for occlusion reasoning. In the method, parts of human objects are detected individually using template matching. Initial detection hypotheses with spatial layout information are represented in a graphical model and refined through a Bayesian estimation. In this paper, mean field method is employed for such an...
In this paper, we propose a novel gait recognition framework which is Spherical Space Model with Human Point Clouds (SSM-HPC). A new gait representation is also introduced, which is called Marching in Place (MIP) gait and preserves the spatiotemporal characteristics of individual gait manner. Various researches for gait recognition have used human silhouette images from moving picture. This research...
Color and depth play important roles in natural scenes and in vision, and their perception is related. Extensive work has been conducted on studying the luminance statistics of natural scenes; however, there is very little work done on analyzing the statistics between luminance and range in natural scenes, not to mention color and range. In this paper, we present the LIVE Color+3D Database, which...
We propose a novel method, called segmentation by temporal detection integration (STDI), to improve the segmentation results of background subtraction. The STDI applies split and merge algorithms forwardly and backwardly to obtain appropriate region segmentations based on the integration of the temporal detections across frames. The proposed scheme can be applied to human detection and tracking to...
Tracking non-rigid objects with significant shape variation in complex scenario is a difficult problem. Human tracking is a special case of this problem since human body has good local rigid properties. In this paper, we propose a novel human tracking method which explores the local rigid properties while keeping the global structure very well. This method consists of three stages. First, the human...
In this paper, we propose a 3D template-based human action detection base on volume pattern matching. A volume pattern is obtained by detecting the principal plane from a space-time patch using the 3D moment-preserving technique. Instead of segmentation and detailed shape representation, the objective of this research is to develop and apply computer vision methods that explore the structure of a...
We propose a new system for building a 3D database for human teeth. Real extracted human teeth are scanned using a cone-beam CT scanner to build. The teeth models are segmented from the resulting images by means of level sets. The database includes 3D models of these teeth after minimizing global differences between the models. An affine transformation function is used to model the differences between...
This paper presents a human detection method using contour-based local motion features. The local motion is encoded using a variant of the popular Local Binary Pattern (LBP) called Non-Redundant Local Binary Pattern (NRLBP) descriptor computed on the difference image of two consecutive frames. In addition, the local motion features are extracted along the human's boundary contour. Localising features...
The main contribution of this paper is a new people detection algorithm based on motion information. The algorithm builds a people motion model based on the Implicit Shape Model (ISM) Framework and the MoSIFT descriptor. We also propose a detection system that integrates appearance, motion and tracking information. Experimental results over sequences extracted from the TRECVID dataset show that our...
As a healthful aerobic exercise, Yoga shall not be exclusive to women and men also needs Yoga for relieving pressure as too much pressure is put on men in the modern fast paced work and life and men have to undertake more duties and liabilities in this society. In this paper, research is conducted into Yoga's functions for men's health and its influence on men's bodies and minds, and through the research,...
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