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Learning to Detect Phone-related Pedestrian Distracted Behaviors with Synthetic Data

Learning to Detect Phone-related Pedestrian Distracted Behav...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Hatay, Emre Ma, Jin Sun, Huiming Fang, Jianwu Gao, Zhiqiang Yu, Hongkai Cleveland State Univ Cleveland OH 44115 USA Changan Univ Xian Peoples R China

ISBN: (纸本)9781665448994

Due to the popularity and mobility of smart phones, phone-related pedestrian distracted behaviors, e.g., Texting, Game Playing, and Phone calls, have caused many traffic fatalities and accidents. As an advanced driver-assistance or autonomous-driving system, computer vision could be used to automatically detect distractions from cameras installed on the vehicle for useful safety intervention. The state-of-the-art method models this problem as a standard supervised learning method with a two-branch Convolutional Neural Network (CNN) followed by a voting on all image frames. In contrast, this paper proposes a new synthetic dataset named SYN-PPDB (448 synchronized video pairs of 53,760 computer game images) for this research problem and models it as a transfer learning problem from synthetic data to real data. A new deep learning model embedded with spatial-temporal feature learning and pose-aware transfer learning is proposed. Experimental results show that we could improve the state-of-the-art overall recognition accuracy from 84.27% to 96.67%.

关键词： computer vision Computational modeling Transfer learning Supervised learning Games pattern recognition Synchronization

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Generative Zero-shot Network Quantization

Generative Zero-shot Network Quantization

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： He, Xiangyu Lu, Jiahao Xu, Weixiang Hu, Qinghao Wang, Peisong Cheng, Jian Chinese Acad Sci Inst Automat Beijing Peoples R China

ISBN: (纸本)9781665448994

Convolutional neural networks are able to learn realistic image priors from numerous training samples in low-level image generation and restoration [66]. We show that, for high-level image recognition tasks, we can further reconstruct "realistic" images of each category by leveraging intrinsic Batch Normalization (BN) statistics without any training data. Inspired by the popular VAE/GAN methods, we regard the zero-shot optimization process of synthetic images as generative modeling to match the distribution of BN statistics. The generated images serve as a calibration set for the following zero-shot network quantizations. Our method meets the needs for quantizing models based on sensitive information, e.g., due to privacy concerns, no data is available. Extensive experiments on benchmark datasets show that, with the help of generated data, our approach consistently outperforms existing data-free quantization methods.

关键词： Training Quantization (signal) Image resolution Image synthesis Training data pattern recognition Image restoration

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Automatic Detection of Body Parts in X-Ray Images

Automatic Detection of Body Parts in X-Ray Images

引用

ieee-computer-society conference on computer vision and pattern recognition workshops

作者： Jeanne, Vincent Unay, Devrim Jacquet, Vincent Philips Res Labs Eindhoven Netherlands ISEN Brest France

ISBN: (纸本)9781424439942

The number of digital images that needs to be acquired, analyzed, classified, stored and retrieved in the medical centers is exponentially growing with the advances in medical imaging technologic Accordingly medical image classification and retrieval has become a popular topic in the recent years. Despite many projects,focusing on this problem, proposed solutions are still far from being sufficiently accurate for real-life implementations. Interpreting medical image classification and retrieval as a multi-class classification task, in this work, we investigate the performance of five different feature types in a SVM-based learning framework-for classification of human body X-Ray images into classes corresponding to body parts. Our comprehensive experiments,show that four conventional feature types provide performances comparable to the literature with low per-class accuracies, whereas local binary patterns produce not only very good global accuracy but also good class-specific accuracies with respect to the features used in the literature.

关键词： Local binary pattern

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Robust Real-Time 3D Modeling of Static Scenes Using Solely a Time-of-Flight Sensor

Robust Real-Time 3D Modeling of Static Scenes Using Solely a...

引用

ieee-computer-society conference on computer vision and pattern recognition workshops

作者： Feulner, Johannes Penne, Jochen Kollorz, Eva Hornegger, Joachim Univ Erlangen Nurnberg Chair Pattern Recognit D-8520 Erlangen Germany

ISBN: (纸本)9781424439942

An algorithm is proposed for the 3D modeling of static scenes solely based on the range and intensity data acquired by a Time-of-Flight camera during an arbitrary movement. No additional scene acquisition devices, like inertia sensor, positioning robots or intensity based cameras are incorporated. The current pose is estimated by maximizing the uncentered correlation coefficient between edges detected in the current and a preceding frame at a minimum frame rate of four fps and an average accuracy of 45 mm. The paper also describes several extensions for robust registration like multiresolution hierarchies and projection Iterative Closest Point algorithm. The basic registration algorithm and its extensions were intensively evaluated against ground truth data to validate the accuracy, robustness and real-time-capability.

关键词： 3D modeling 3D reconstruction ToF camera Time-of-Flight

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Adapting a Pedestrian Detector by Boosting LDA Exemplar Classifiers

Adapting a Pedestrian Detector by Boosting LDA Exemplar Clas...

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26th ieee conference on computer vision and pattern recognition (CVPR)

作者： Xu, Jiaolong Vazquez, David Ramos, Sebastian Lopez, Antonio M. Ponsa, Daniel Autonomous Univ Barcelona Comp Vis Ctr E-08193 Barcelona Spain

ISBN: (纸本)9780769549903

Training vision-based pedestrian detectors using synthetic datasets (virtual world) is a useful technique to collect automatically the training examples with their pixel-wise ground truth. However, as it is often the case, these detectors must operate in real-world images, experiencing a significant drop of their performance. In fact, this effect also occurs among different real-world datasets, i.e. detectors' accuracy drops when the training data (source domain) and the application scenario (target domain) have inherent differences. Therefore, in order to avoid this problem, it is required to adapt the detector trained with synthetic data to operate in the real-world scenario. In this paper, we propose a domain adaptation approach based on boosting LDA exemplar classifiers from both virtual and real worlds. We evaluate our proposal on multiple real-world pedestrian detection datasets. The results show that our method can efficiently adapt the exemplar classifiers from virtual to real world, avoiding drops in average precision over the 15%.

关键词： computer vision object detection pedestrians statistical analysis

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Yoga-82: A New Dataset for Fine-grained Classification of Human Poses

Yoga-82: A New Dataset for Fine-grained Classification of Hu...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Verma, Manisha Kumawat, Sudhakar Nakashima, Yuta Raman, Shanmuganathan Osaka Univ Osaka Japan Indian Inst Technol Gandhinagar Gandhinagar India

ISBN: (纸本)9781728193601

Human pose estimation is a well-known problem in computer vision to locate joint positions. Existing datasets for learning of poses are observed to be not challenging enough in terms of pose diversity, object occlusion and view points. This makes the pose annotation process relatively simple and restricts the application of the models that have been trained on them. To handle more variety in human poses, we propose the concept of fine-grained hierarchical pose classification, in which we formulate the pose estimation as a classification task, and propose a dataset, Yoga-82, for large-scale yoga pose recognition with 82 classes. Yoga-82 consists of complex poses where fine annotations may not be possible. To resolve this, we provide hierarchical labels for yoga poses based on the body configuration of the pose. The dataset contains a three-level hierarchy including body positions, variations in body positions, and the actual pose names. We present the classification accuracy of the state-of-the-art convolutional neural network architectures on Yoga-82. We also present several hierarchical variants of DenseNet in order to utilize the hierarchical labels.

关键词： computer vision

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Gated Recurrent Unit-Based RNN for Remote Photoplethysmography Signal Segmentation

Gated Recurrent Unit-Based RNN for Remote Photoplethysmograp...

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ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Sabour, Rita Meziati Benezeth, Yannick Univ Bourgogne Franche Comte Dijon France Univ Bourgogne Franche Comte ImViA Lab Dijon France

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Remote Photoplethysmography (rPPG) enables quantifying blood volume variations in the skin tissues from an input video recording, using a regular RGB camera. Obtained pulse signals often contain noisy portions due to motion, leading researchers to put aside a great number of rPPG signals in their studies. In this paper, an approach using a Gated Recurrent Unit-based neural network model in order to identify reliable portions in rPPG signals is proposed. This is done by classifying rPPG signal samples into reliable and unreliable samples. For this purpose, rPPG and electrocardiography signals (ECG) were collected from 11 participants, rPPG signal samples were labeled (ECG was used as ground truth), and data were augmented to reach a total number of 11000 1-minute-long rPPG signals. We developed a model composed of a unidimensional CNN and a Bidirectional GRU (1D-CNN+B-GRU) for this study, and obtained an accuracy rate of 85.88%.

关键词： computer network reliability Neural networks Electrocardiography Logic gates Photoplethysmography Skin pattern recognition

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PromptSync: Bridging Domain Gaps in vision-Language Models through Class-Aware Prototype Alignment and Discrimination

PromptSync: Bridging Domain Gaps in Vision-Language Models t...

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ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Khandelwal, Anant Glance AI Bangalore Karnataka India

ISBN: (纸本)9798350365474

The potential for zero-shot generalization in vision-language (V-L) models such as CLIP has spurred their widespread adoption in addressing numerous downstream tasks. Previous methods have employed test-time prompt tuning to adapt the model to unseen domains, but they overlooked the issue of imbalanced class distributions. In this study, we explicitly address this problem by employing class-aware prototype alignment weighted by mean class probabilities obtained for the test sample and filtered augmented views. Additionally, we ensure that the class probabilities are as accurate as possible by performing prototype discrimination using contrastive learning. The combination of alignment and discriminative loss serves as a geometric regularizer, preventing the prompt representation from collapsing onto a single class and effectively bridging the distribution gap between the source and test domains. Our method, named PromptSync, synchronizes the prompts for each test sample on both the text and vision branches of the V-L model. In empirical evaluations on the domain generalization benchmark, our method outperforms previous best methods by 2.33% in overall performance, by 1% in base-to-novel generalization, and by 2.84% in cross-dataset transfer tasks.

关键词： Visual languages

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FPGA-based fast response image analysis for autonomous or semi-autonomous indoor flight

FPGA-based fast response image analysis for autonomous or se...

引用

27th ieee conference on computer vision and pattern recognition (CVPR)

作者： Ladig, Robert Shimonomura, Kazuhiro Ritsumeikan Univ Dept Robot Kusatsu Shiga 5258577 Japan

ISBN: (纸本)9781479943098

Small aerial vehicles, like quadrotor, have a high potential to be helpful tools in first response scenarios like earthquakes, landslides and fires. But even simple tasks like holding position and altitude can be challenging to accomplish by a human operator and even more challenging autonomously. When outdoors, using GPS and pressure sensors is feasible, but indoors or in GPS denied environments it is not. Until now, for indoor flight scenarios either a lot of energy consuming sensors and hardware or a perfectly defined surrounding is required. In this approach, the viability of an onboard FPGA based indoor flight navigation system with a pan-tilt camera mount and a single VGA camera is tested. It can be used to either support an operator performing a hold position and altitude task, or act completely autonomously to achieve this task.

关键词： Aerial robotics FPGA Monocular vision Onboard vision Quadrotor Monocular vision Field programmable gate arrays flight Global Positioning Systems Pressure Sensor Device Component FAST-RESPONSE INDOORS Outdoors

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Teaching computer vision and its Societal Effects: A Look at Privacy and Security Issues from the Students' Perspective 30

Teaching Computer Vision and its Societal Effects: A Look at...

引用

30th ieee/CVF conference on computer vision and pattern recognition workshops (CVPRW)

作者： Cote, Melissa Albu, Alexandra Branzan Univ Victoria Victoria BC Canada

ISBN: (纸本)9781538607336

In this paper, we look at the societal effects of computer vision technologies from the perspective of the future minds in computer vision: senior year engineering students. Engineering education has traditionally focused on technical skills and knowledge. Nowadays, the need for educating engineers in socio-technical skills and reflective thinking, especially on the bright and dark sides of the technology they develop, is being recognized. We advocate for the integration of social awareness modules into computer vision courses so that the societal effects of technology can be studied together with the technology itself, as opposed to the often more generic 'impact of technology on society' courses. Such modules provide a venue for students to reflect on the real-world consequences of technology in concrete, practical contexts. In this paper, we present qualitative results of an observational study analyzing essays of senior year engineering students, who wrote about societal impacts of computer vision technologies of their choice. Privacy and security issues ranked as the top impact topics discussed by students among 50 topics. Similar social awareness modules would apply well to other advanced technical courses of the engineering curriculum where privacy and security are a major concern, such as big data courses. We believe that such modules are highly likely to enhance the reflective abilities of engineering graduates regarding societal impacts of novel technologies.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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