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2006 9th International Conference on Information Fusion, FUSION

作者： Frank Hsu, D. Lyons, Damian M. Ai, Jizhou Computer Vision and Robotics Laboratory Department of Computer and Information Science Fordham University Bronx NY 10458 United States

ISBN: (纸本)1424409535

In many useful video tracking situations, targets move through repeated mutual occlusions. As targets undergo occlusions, the feature subsets and combinations of those features that are effective in identifying the target and improving tracking performance may change. We use Combinatorial Fusion Analysis to select and evaluate criteria by which to identify the combination of features that will produce the most accurate tracking. In particular we show that the combination of a pair of features A and B will improve the accuracy only if (a) A and B have relative high performance, and (b) A and B are diverse. We present experimental results from three diverse video sequences to illustrate the performance of the proposed criteria.

关键词： Target tracking

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Generative 3D hand tracking with spatially constrained pose sampling 28

Generative 3D hand tracking with spatially constrained pose ...

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28th British Machine vision Conference, BMVC 2017

作者： Roditakis, Konstantinos Makris, Alexandros Argyros, Antonis A. Computational Vision and Robotics Laboratory Institute of Computer Science FORTH Greece Computer Science Department University of Crete Greece

ISBN: (纸本)190172560X

We present a method for 3D hand tracking that exploits spatial constraints in the form of end effector (fingertip) locations. The method follows a generative, hypothesize-and-test approach and uses a hierarchical particle filter to track the hand. In contrast to state of the art methods that consider spatial constraints in a soft manner, the proposed approach enforces constraints during the hand pose hypothesis generation phase by sampling in the Reachable Distance Space (RDS). This sampling produces hypotheses that respect both the hands’ dynamics and the end effector locations. The data likelihood term is calculated by measuring the discrepancy between the rendered 3D model and the available observations. Experimental results on challenging, ground truth-annotated sequences containing severe hand occlusions demonstrate that the proposed approach outperforms the state of the art in hand tracking accuracy. © 2017. The copyright of this document resides with its authors.

关键词： End effectors

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Sharing and fusing landmark information in a team of autonomous robots

Sharing and fusing landmark information in a team of autonom...

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Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2009

作者： Lyons, Damian M. Robotics and Computer Vision Laboratory Department of Computer and Information Science Fordham University Bronx NY 10458 United States

ISBN: (纸本)9780819476111

A team of robots working to explore and map a space may need to share information about landmarks so as register local maps and to plan effective exploration strategies. In this paper we investigate the use of spatial histograms (spatiograms) as a common representation for exchanging landmark information between robots. Each robot can use sonar, stereo, laser and image information to identify potential landmarks. The sonar, laser and stereo information provide the spatial dimension of the spatiogram in a landmark-centered coordinate frame while video provides the image information. We call the result a terrain spatiogram. This representation can be shared between robots in a team to recognize landmarks and to fuse observations from multiple sensors or multiple platforms. We report experimental results sharing indoor and outdoor landmark information between a two different models of robot equipped with differently configured stereocameras and show that the terrain spatiogram (1) allows the robots to recognize landmarks seen only by the other with high confidence and, (2) allows multiple views of a landmark to be fused in a useful fashion. © 2009 SPIE.

关键词： Mobile robots

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A vision Based Hardware-Software Real-Time Control System for the Autonomous Landing of an UAV 1

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International Conference on computer vision and Graphics, ICCVG 2020

作者： Blachut, Krzysztof Szolc, Hubert Wasala, Mateusz Kryjak, Tomasz Gorgon, Marek Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (数字)9783030590062

ISBN: (纸本)9783030590055

In this paper we present a vision based hardware-software control system enabling the autonomous landing of a multirotor unmanned aerial vehicle (UAV). It allows for the detection of a marked landing pad in real-time for a 1280 720 @ 60 fps video stream. In addition, a LiDAR sensor is used to measure the altitude above ground. A heterogeneous Zynq SoC device is used as the computing platform. The solution was tested on a number of sequences and the landing pad was detected with 96% accuracy. This research shows that a reprogrammable heterogeneous computing system is a good solution for UAVs because it enables real-time data stream processing with relatively low energy consumption. © 2020, Springer Nature Switzerland AG.

关键词： System-on-chip

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Optimisation of a Siamese Neural Network for Real-Time Energy Efficient Object Tracking 1

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International Conference on computer vision and Graphics, ICCVG 2020

作者： Przewlocka, Dominika Wasala, Mateusz Szolc, Hubert Blachut, Krzysztof Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (数字)9783030590062

ISBN: (纸本)9783030590055

In this paper the research on optimisation of visual object tracking using a Siamese neural network for embedded vision systems is presented. It was assumed that the solution shall operate in real-time, preferably for a high resolution video stream, with the lowest possible energy consumption. To meet these requirements, techniques such as the reduction of computational precision and pruning were considered. Brevitas, a tool dedicated for optimisation and quantisation of neural networks for FPGA implementation, was used. A number of training scenarios were tested with varying levels of optimisations – from integer uniform quantisation with 16 bits to ternary and binary networks. Next, the influence of these optimisations on the tracking performance was evaluated. It was possible to reduce the size of the convolutional filters up to 10 times in relation to the original network. The obtained results indicate that using quantisation can significantly reduce the memory and computational complexity of the proposed network while still enabling precise tracking, thus allow to use it in embedded vision systems. Moreover, quantisation of weights positively affects the network training by decreasing overfitting. © 2020, Springer Nature Switzerland AG.

关键词： Field programmable gate arrays (FPGA)

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Energy Efficient Hardware Acceleration of Neural Networks with Power-of-Two Quantisation

Energy Efficient Hardware Acceleration of Neural Networks wi...

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International Conference on computer vision and Graphics, ICCVG 2022

作者： Przewlocka-Rus, Dominika Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9783031220241

Deep neural networks virtually dominate the domain of most modern vision systems, providing high performance at a cost of increased computational complexity. Since for those systems it is often required to operate both in real-time and with minimal energy consumption (e.g., for wearable devices or autonomous vehicles, edge Internet of Things (IoT), sensor networks), various network optimisation techniques are used, e.g., quantisation, pruning, or dedicated lightweight architectures. Due to the logarithmic distribution of weights in neural network layers, a method providing high performance with significant reduction in computational precision (for 4-bit weights and less) is the Power-of-Two (PoT) quantisation (and therefore also with a logarithmic distribution). This method introduces additional possibilities of replacing the typical for neural networks Multiply and ACcumulate (MAC—performing, e.g., convolution operations) units, with more energy-efficient Bitshift and ACcumulate (BAC). In this paper, we show that a hardware neural network accelerator with PoT weights implemented on the Zynq UltraScale + MPSoC ZCU104 SoC FPGA can be at least 1.4x more energy efficient than the uniform quantisation version. To further reduce the actual power requirement by omitting part of the computation for zero weights, we also propose a new pruning method adapted to logarithmic quantisation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： System-on-chip

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Traffic Sign Classification Using Deep and Quantum Neural Networks

Traffic Sign Classification Using Deep and Quantum Neural Ne...

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International Conference on computer vision and Graphics, ICCVG 2022

作者： Kuros, Sylwia Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9783031220241

Quantum Neural Networks (QNNs) are an emerging technology that can be used in many applications including computer vision. In this paper, we presented a traffic sign classification system implemented using a hybrid quantum-classical convolutional neural network. Experiments on the German Traffic Sign Recognition Benchmark dataset indicate that currently QNN do not outperform classical DCNN (Deep Convolutuional Neural Networks), yet still provide an accuracy of over 90% and are a definitely promising solution for advanced computer vision. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Traffic signs

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Efficient background modeling through incremental Support Vector Data Description

Efficient background modeling through incremental Support Ve...

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作者： Tavakkoli, Alireza Nicolescu, Mircea Bebis, George Nicolescu, Monica Computer Vision Laboratory University of Nevada Reno United States Robotics Laboratory University of Nevada Reno United States

ISBN: (纸本)9781424421756

Background modeling is an essential and important part of many high-level video processing applications. Recently, the Support Vector Data Description (SVDD) has been introduced for novelty detection when only one class of data is available, i.e. background pixels. This paper proposes a method to efficiently train an SVDD and compares the performance of this training algorithm with the traditional SVDD training techniques. We compare the performance of our method with traditional SVDD and other classification algorithms on various data sets including real video sequences. © 2008 IEEE.

关键词： Data description

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The "Castelet": A dynamically reconfigurable stage for performing arts 07

The "Castelet": A dynamically reconfigurable stage for perfo...

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ACM SIGGRAPH 2007 Sketches, SIGGRAPH'07

作者： Jobin, Jean-Philippe Comtois, Sylvain Gosselin, Clément Faguy, Robert Laurendeau, Denis Robotics Laboratory Computer Vision and Systems Lab. LANTISS Laval University Quebec City Canada

The hero jumped down the wall, escalated the hill, slid down the rock, climbed the stairs and finally left the vilain behind...In this classical scene, the hero has to move on different types of terrain. Recreating su...

ISBN: (纸本)9781450347266

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SAGE: A decision support system for the sequencing of operations within a robotic workcell

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Decision Support Systems 1988年第3期4卷 329-343页

作者： Freedman, P. Malowany, A. Computer Vision and Robotics Laboratory McGill Research Centre for Intelligent Machines McGill University Montréal Que. Canada

This paper describes a new approach to decision support based on logic programming. SAGE, Sequence Analysis by Graphical Evaluation, is a both a logic framework and a set of Prolog programs to express and then solve the problem of repetitive sequencing of operations within a robotics workcell. We create a Timed Petri Net from the user description consisting of the initial state of the workcell, plus the operations to be performed. Each operation is defined by (i) the command to be executed, (ii) a list of enabling conditions, (iii) a list of changes made to the state of the workcell by executing the command, and (iv) its relative integer duration. After some preliminary analysis, this net is used to generate the Task Space of all feasible time histories of workcell events. Repetitive sequences of all the workcell operations are then constructed from cycles in the Task space. From the feasible sequences thus identified, the time-optimal one is selected. SAGE clearly demonstrates both the power of symbolic expression, and the power of pattern matching as a basis for decision support systems. © 1988.

关键词： Petri Nets Prolog robotics

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