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A general approach is proposed to determine the occupancy in a room using sensor data and knowledge coming respectively from observation and questioning are determined. Means to estimate occupancy include motion detections, power consumption and and acoustic pressure rewarded by a micro-phone. The proposed approach is inspired from machine learning. It starts by determining the most useful measurements...
Research in sentiment analysis, as defined, goes for classifying obstinate writings as per the extremity of the sentiment communicated. On the other hand, contingent upon the final utilization of the sentiment analysis errand, order of opinion is carried out at diverse levels. Case in point, when a user is keen on figuring out opinions individuals gave around a film, the general sentiment is sufficient...
Many disaster warning and response systems can improve their surveillance coverage of the threatened area by supplementing in situ and remote physical sensor data with crowdsourced human sensor data captured and sent by people in the area. This paper presents fusion methods which enable a crowdsourcing enhanced system to use human sensor data and physical sensor data synergistically to improve its...
CCTV is one of the tools that can be used to extract the needed traffic Information. Extracted information from image sequences of CCTV can give us real information about the number of passing vehicles and vehicles speed. In this paper we propose a new method in detecting the number of vehicles and vehicle speed measurement in low light conditions. Headlight detection is used in order to identify...
In this paper, we present an algorithm that is to estimate the position of a hand-held camera with respect to terrestrial LiDAR data. Our input is a set of 3D range scans with intensities and one or a set of 2D uncalibrated camera images of the scene. The algorithm that automatically registers range scans and 2D images is composed of following steps. In the first step, we project the terrestrial LiDAR...
This paper addresses the multimodal nature of social dominance and presents multimodal fusion techniques to combine audio and visual nonverbal cues for dominance estimation in small group conversations. We combine the two modalities both at the feature extraction level and at the classifier level via score and rank level fusion. The classification is done by a simple rule-based estimator. We perform...
We propose a method for deblurring of spatially variant object motion. A principal challenge of this problem is how to estimate the point spread function (PSF) of the spatially variant blur. Based on the projective motion blur model of, we present a blur estimation technique that jointly utilizes a coded exposure camera and simple user interactions to recover the PSF. With this spatially variant PSF,...
We present a novel segment extraction and segment-based depth estimation technique. Proposed segment extraction technique exploits depth and motion information of segments between frames as well as color information. We firstly divide each frame of reference view into foreground and background areas based on initial depth information obtained from time-of-flight (TOF) camera. Then we extract segments...
This paper describes the crowd image analysis challenge that forms part of the PETS 2009 workshop. The aim of this challenge is to use new or existing systems for i) crowd count and density estimation, ii) tracking of individual(s) within a crowd, and iii) detection of separate flows and specific crowd events, in a real-world environment. The dataset scenarios were filmed from multiple cameras and...
The purpose of this paper is to estimate the position of a human in the image frame and to use this information to diagnose falls. A nonholonomic locomotion model describes the displacement of the human due to the similarities between human and nonholonomic mobile robot displacements. To estimate the human position in the world frame, the principle of Receding Horizon Estimation (RHE) is extended...
This paper presents a novel visual servoing strategy for a nonholonomic mobile robot, which is based on a new motion estimation technique. By taking into account the planar motion constraint of mobile robots, the proposed motion estimation technique does not require the estimation and decomposition of the homography or fundamental matrix, and it dose not cause any ambiguity problems. Moreover, the...
A number of problems in computer vision require the estimation of a set of matrices, each of which is defined only up to an individual scale factor and represents the parameters of a separate model, under the assumption that the models are intrinsically interconnected. One example of such a set is a family of fundamental matrices sharing an infinite homography. Here an approach is presented to estimating...
Reliably tracking people throughout a camera network is an important capability in areas such as law enforcement, homeland protection, and healthcare. In this paper we will provide an overview of GE Global Research's tracking system and evaluate it against a subset of the PETS 2009 dataset. The tasks of counting, density estimation, multiperson tracking as well as the tracking of selected individuals...
In this work, we present a new robust method for calibrating the vision system. With the known intrinsic parameters of the camera, we show that its motion parameters, in terms of translation vector and rotation matrix, can be determined automatically from plane-based homography. In this method, a closed-form solution is provided to increase the computational efficiency and arbitrary motion is allowed...
The projective recovery of 3D point structure from multiple images has been one of the classical problems in computer vision. Existing methods for projective reconstruction usually require a priori estimation of a consistent set of projective depths which in turn require the estimation of the projection matrices or the fundamental matrices in advance. Those methods are usually nonlinear, time-consuming,...
A modified covariance extended Kalman filter (MVEKF) algorithm is proposed to the monocular simultaneous localization and mapping (SLAM) in this paper. Recent literatures have shown that it is possible to solve the monocular SLAM using the Extended Kalman Filter (EKF) and the inverse-depth parameterization. However, the EKF algorithm has its intrinsic disadvantage such as the divergence. Here we propose...
This paper is about calibrating the relative poses of a group of rigidly co-located calibrated cameras. The cameras need not share any common field-of-view. A 3D test field of stationary point targets is used and the group of cameras is moved to a number of positions in the test field. The target positions need not be known exactly as they adjust during calibration. A non-linear solution is developed...
Detection and analysis of trajectories are effective for providing services to pedestrians in public spaces. We have proposed a method to detect moving objects from a monocular image sequence with a normal mixture model. However, the method cannot accommodate a changing number of moving objects. As described herein, to overcome this shortcoming, we proposed two algorithms for counting number of moving...
Ambient intelligence systems need to know what the users are doing. In this paper, An architecture for human activity recognition using a visual sensor network is proposed. The video sequence perceived by each camera is locally processed to obtain a local activity label. These activity labels are fused by an upper tier to obtain a global activity label. The activities recognized by the system are...
This paper describes a particle filter based approach for estimating the ground plane from an image sequence. Based on a Bayesian framework, the particle filter provides a robust estimation of the plane parameters, since it can handle non-linearities, while allowing a high flexibility for integrating new cues into the system. Furthermore, the different modes of the resulting probability density function...
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