We define corner points in an image as the intersections among detected straight line segments, and propose an algorithm that detects corners from such a definition. Our corner detection algorithm CLDC then makes use ...
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We define corner points in an image as the intersections among detected straight line segments, and propose an algorithm that detects corners from such a definition. Our corner detection algorithm CLDC then makes use of the LDC (Line detection using Contours) algorithm from, which outputs the list of all detected line segments together with their endpoints. Each line segment is extended in a post-processing step. CLDC (Corners from LDC) then finds corners in O((n + I)log n) time, where n and I are the number of endpoints the intersections of line segments, respectively. Detected corners are linked via line segments that define them. Such an output of the corner detection algorithm is a novel concept. The algorithm is comparable in time complexity with other algorithms, while providing more information about the line segments in the image. CLDC is robust to image transformations, such as rotation and translations. Our CLDC is compared to some existing algorithm, and its advantages are demonstrated.
This paper describes in details the performance of an advanced detecting algorithm for multi-sensor target Track Before detection (TBD) through the Hough Transform (HT). The detection algorithm employs the idea of usi...
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ISBN:
(纸本)9781424458110;9781424458127
This paper describes in details the performance of an advanced detecting algorithm for multi-sensor target Track Before detection (TBD) through the Hough Transform (HT). The detection algorithm employs the idea of using the Hough Transform for joint detection of linear trajectory targets. The polar modification of the TBD-HT approach is applied to a multi-sensor Polar Hough detector for multi-sensor target/trajectory detection in ECM environment with a Stand-off-Jammer (SOJ). A CFAR detector is proposed for signal detection in the (r-t) space instead of fixed thresholding in order to enhance the target detectability in ECM environment. In this paper a centralized structure of a multi-sensor Polar Hough detector is considered. The expressions calculating the probability characteristics, i.e. the probability of target/trajectory detection and the false alarm probability, are analytically derived. The multi-channel TBD-HT detector probability characteristics are compared with those for the conventional signal processing.
Human detection is a task met in many applications such as surveillance & security, safe driving system, intelligent vehicles, etc.. It is more complicated compared to the detection of car and other targets, due t...
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Human detection is a task met in many applications such as surveillance & security, safe driving system, intelligent vehicles, etc.. It is more complicated compared to the detection of car and other targets, due to the variety of poses and external appearance of human bodies. This paper presents an adaboost human detection algorithm and its implementation on a DSP platform. The detector uses haar-like features as classifiers. A cascade of boosted classifiers is obtained after extensive training of hundreds of positive and negative samples. Experimental results with the adaboost human detection algorithm are presented in the paper.
In recent publications, some special detectors were proposed to improve the performance and complexity gaps between the optimal detector and the suboptimal detector. In this paper, we propose a multistage chase detect...
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In recent publications, some special detectors were proposed to improve the performance and complexity gaps between the optimal detector and the suboptimal detector. In this paper, we propose a multistage chase detection algorithm for MIMO-OFDM systems, which use chase detection framework to design sub-detector, so the nest chase detection was implemented that can further decrease the error spread and improve the BER performance. Simulation results show that the proposed schemes performs better than BLAST and conventional chase detection, which can achieve near-ML performance with lower complexity compared with ML algorithm.
We propose a robust mesh-to-mesh collision detection algorithm using a ray tracing method. The algorithm checks all vertices of a geometrical object based on the proposed criteria, and then the colliding vertices are ...
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We propose a robust mesh-to-mesh collision detection algorithm using a ray tracing method. The algorithm checks all vertices of a geometrical object based on the proposed criteria, and then the colliding vertices are detected. In order to realize a real-time calculation, acceleration by spatial subdivision is performed. Since the proposed ray-traced collision detection method can directly calculate the reacting forces between the colliding objects, this method is apt for a real-time medical simulation dealing with deformable organs. Our method addresses the limitation of the previous ray-traced approach as it can detect collisions between all arbitrarily shaped objects, including non-convex or sharp objects. Moreover, deeply penetrated collisions can be detected effectively.
This paper shows a new approach to significantly improve the runtime behaviour of existing object pose detection algorithms. The idea of anticipation-preprocessing is to reduce possible object poses up to a minimum by...
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ISBN:
(纸本)9781617387197
This paper shows a new approach to significantly improve the runtime behaviour of existing object pose detection algorithms. The idea of anticipation-preprocessing is to reduce possible object poses up to a minimum by limiting the solution space. The assumption is that a smaller solution space comes along with a much faster evaluation. Anticipation-preprocessing starts with the most obvious features of sensory input. The treatment of features takes gestalt law of organization [1] into account. Based on that, the procedure is to find new features and to keep recombining them. With the aid of the achieved feature sets a conclusion about a solution subspace can be drawn. Anticipation-preprocessing is inspired by human visual perception, whereof several theories exist. Comparing to one of the most famous by Marr [2], memorization influences the entire process of the new approach and not just the final matching. The new approach was tested with an object pose detection algorithm called Coherent-Distance-Characteristics (abbr.: CDC) [3]. CDC Object Pose detection is a view based approach which uses compact object description and still provides strong reliability. It has been originally developed for bin-picking applications by the authors. CDC works on spatial depth data. It was shown that the use of just one or two features already results in a runtime reduction of about 90 percent.
Several normalized least mean square (NLMS) based minimum mean square error (MMSE) adaptive detection algorithms have been proposed in recent years in order to mitigate the inter symbol interference (ISI) in the ultra...
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Several normalized least mean square (NLMS) based minimum mean square error (MMSE) adaptive detection algorithms have been proposed in recent years in order to mitigate the inter symbol interference (ISI) in the ultra wideband (UWB) systems. In this paper, we propose an improved NLMS (INLMS) based MMSE adaptive detection algorithm that can choose different step size adaptively and can solve the conflicting requirement of existing NLMS based algorithms. Simulation results show that bit error rate (BER) performance of the proposed algorithm is better than existing algorithms with the same training sequence length. Also when the training sequence length is longer than the steady state length of existing algorithms, the BER performance of the proposed algorithm can be improved by increasing the training sequence length which can't be achieved by existing algorithms.
In this paper, an efficient sphere decoding algorithm (SDA) applied to solve the inter-symbol-interference (ISI) data detection problem is proposed. This proposed algorithm takes advantages of the SDA to obtain the so...
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ISBN:
(纸本)9781424425181;9781424425198
In this paper, an efficient sphere decoding algorithm (SDA) applied to solve the inter-symbol-interference (ISI) data detection problem is proposed. This proposed algorithm takes advantages of the SDA to obtain the solution close to ML solution with the simplified K-best tree search method for the ISI data detection under ISI effect. Compared with the frequency-domain MMSE or Zero-Forcing equalization techniques for SCBT (Single-Carrier Block Transmission) systems, this algorithm can perform at least 1.5dB better than frequency- domain equalizers under the environment of randomly generated channel impulse responses.
Data mining techniques were applied for the reduction of false positives in aviation explosives detection CT (computed tomography) imaging systems. An inductive post-detection classifier (PDC) was trained, implemented...
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Data mining techniques were applied for the reduction of false positives in aviation explosives detection CT (computed tomography) imaging systems. An inductive post-detection classifier (PDC) was trained, implemented, and fielded. The PDC can only eliminate alarms generated from the existing detection system - it does not detect new alarms.
作者:
Terje JohnsenFFI
Norwegian Defence Research Establishment Kjeller Norway
This paper analyses two SAR images recorded on different dates of the same container harbor. To understand the detailed structure and stacking order of different areas of the harbor, theoretical and model studies has ...
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ISBN:
(纸本)9781424458110;9781424458127
This paper analyses two SAR images recorded on different dates of the same container harbor. To understand the detailed structure and stacking order of different areas of the harbor, theoretical and model studies has been applied. These studies revealed the predominant scattering regions of container stacks. This knowledge is used to quantify stacking heights, orientation and steps in the container structure of the two TerraSAR-X SAR magnitude images. Calculations from a change detection algorithm provided an image that emphasized regions in the two where major changes to the stacking configuration were observed. Detailed analysis is focused on a few selected regions resulting in knowledge of numbers of containers moved and structure in the clusters.
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