Pose estimation algorithms with regard to both monocular vision and binocular one have been studied respectively since about twenty years ago, however, few researchers considered comparing two representative methods f...
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ISBN:
(纸本)9781601320438
Pose estimation algorithms with regard to both monocular vision and binocular one have been studied respectively since about twenty years ago, however, few researchers considered comparing two representative methods for the sake of actual application. In this paper, considering the factual model, we have done a comparative study about these two methods quantitatively. The statistical result of calculated error based on simulation experiments denotes that the model-based monocular vision behaves more outstanding than the binocular vision on the computational accuracy and robust inasmuch the monocular vision introduces the known object model in the process of computing the coordinates of feature points. The simulated result has certain guided significance for choosing a suitable pose estimation algorithm in actual engineering projects.
This paper presents an integrated region-based and gradient-based supervised method for segmentation of a patient magnetic resonance images (MRI) of the shoulder joint. The method is noninvasive, anatomy-based and req...
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This paper presents a vision based gesture recognition system for human-robot symbiosis. The system is based on the visual information of the face and is commenced with the recognition of face gesture by connected com...
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ISBN:
(纸本)9781424415502
This paper presents a vision based gesture recognition system for human-robot symbiosis. The system is based on the visual information of the face and is commenced with the recognition of face gesture by connected component analysis of the skin color segmentation of images in HSV color model and neural network based pattern-matching strategies. On gesture recognition, robot is being instructed to perform certain tasks by issuing commands. The system is capable of recognizing static gestures comprised of the face poses, and dynamic gestures of face in motion. The effectiveness of the system has been justified over some experiments. The system has been demonstrated with an entertainment robot named "AlBO" as a human-robot symbiotic relationship.
In this paper, we designed and implemented the image processing board, which inspects the parts if the automobile used stereo vision. Image processing board is composed of a DSP, decoder, memory parts, serial communic...
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ISBN:
(纸本)9781601320438
In this paper, we designed and implemented the image processing board, which inspects the parts if the automobile used stereo vision. Image processing board is composed of a DSP, decoder, memory parts, serial communication part and I·O part. Input a stereo images and process image registration, and then calculated Disparity. Compared disparity values and separate into good or error parts of the automobile. The performance of the designed image processing board was verified by implemented system for experiments. Experiment results show that automatic inspection equipment used image processing board more faster than manual and this equipment run high accuracy and stable inspection.
This paper contains a field report on using model-based design techniques for developing embedded vision applications. A lane border detection algorithm was chosen as target application for testing the design approach...
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ISBN:
(纸本)9780889866461
This paper contains a field report on using model-based design techniques for developing embedded vision applications. A lane border detection algorithm was chosen as target application for testing the design approach. The algorithm detects the lane borders, which marks the drivable area in front of a vehicle. It is an algorithm for an autonomous vehicle which participated in the Defense Advanced Research Projects Agency (DARPA) Grand Challenge 2005. The algorithm was processed on an embedded stereo vision system which was mounted on that vehicle. This paper describes the assembly of the vehicle, the principles of model-based design, the development of the lane border detection algorithm and its functional behavior. Furthermore, it presents evaluation results and our experiences with this design approach.
A Modified Direct Method for the computation of the Zernike moments is presented in this paper. The presence of many factorial terms, in the direct method for computing the Zernike moments, makes their computation pro...
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A Modified Direct Method for the computation of the Zernike moments is presented in this paper. The presence of many factorial terms, in the direct method for computing the Zernike moments, makes their computation process a very time consuming task. Although the computational power of the modern computers is impressively increasing, the calculation of the factorial of a big number is still an inaccurate numerical procedure. The main concept of the present paper is that, by using Stirling's Approximation formula for the factorial and by applying some suitable mathematical properties, a novel, factorial-free direct method can be developed. The resulted moments are not equal to those computed by the original direct method, but they are a sufficiently accurate approximation of them. Besides, their variability does not affect their ability to describe uniquely and distinguish the objects they represent. This is verified by patternrecognition simulation examples. (C) 2007 Elsevier Inc. All rights reserved.
This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothesis that a careful analysis of visible...
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This paper addresses the problem of object detection and recognition in complex scenes, where objects are partially occluded. The approach presented herein is based on the hypothesis that a careful analysis of visible object details at various scales is critical for recognition in such settings. In general, however, computational complexity becomes prohibitive when trying to analyze multiple sub-parts of multiple objects in an image. To alleviate this problem, we propose a generative-model framework-namely, dynamic tree-structure belief networks (DTSBNs). This framework formulates object detection and recognition as inference of DTSBN structure and image-class conditional distributions, given an image. The causal (Markovian) dependencies in DTSBNs allow for design of computationally efficient inference, as well as for interpretation of the estimated structure as follows: each root represents a whole distinct object, while children nodes down the sub-tree represent parts of that object at various scales. Therefore, within the DTSBN framework, the treatment and recognition of object parts requires no additional training, but merely a particular interpretation of the tree/subtree structure. This property leads to a strategy for recognition of objects as a whole through recognition of their visible parts. Our experimental results demonstrate that this approach remarkably outperforms strategies without explicit analysis of object parts. (c) 2006 Elsevier Inc. All rights reserved.
Pedestrian detection from images of the visible spectrum is a high relevant area of research given its potential impact in the design of pedestrian protection systems. There are many proposals in the literature but th...
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ISBN:
(纸本)9783540728467
Pedestrian detection from images of the visible spectrum is a high relevant area of research given its potential impact in the design of pedestrian protection systems. There are many proposals in the literature but they lack a comparative viewpoint. According to this, in this paper we first propose a common framework where we fit the different approaches, and second we use this framework to provide a comparative point of view of the details of such different approaches, pointing out also the main challenges to be solved in the future. In summary, we expect this survey to be useful for both novel and experienced researchers in the field. In the first case, as a clarifying snapshot of the state of the art;in the second, as a way to unveil trends and to take conclusions from the comparative study.
Robust and accurate people tracking is a key task in many promising computer-vision applications. One must deal with non-rigid targets in open-world scenarios, whose shape and appearance evolve over time. Targets may ...
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ISBN:
(纸本)9783540728467
Robust and accurate people tracking is a key task in many promising computer-vision applications. One must deal with non-rigid targets in open-world scenarios, whose shape and appearance evolve over time. Targets may interact, causing partial or complete occlusions. This paper improves tracking by means of particle filtering, where occlusions are handled considering the target's predicted trajectories. Model drift is tackled by careful updating, based on the history of likelihood measures. A colour-based likelihood, computed from histogram similarity, is used. Experiments are carried out using sequences from the CAVIAR database.
A scheme, named tower of knowledge (ToK), is proposed for interpreting 3D scenes. The ToK encapsulates causal dependencies between object appearance and functionality. We demonstrate it by labelling the components of ...
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