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Salient human detection for robot vision SpringerLink

30/03/2007 Salient human detection. Although most human detection systems can detect people, they can distinguish which humans appear more salient. However, the purpose of our work was to develops a salient human detection system for indoor environments. First, the steps for detecting salient objects proceeded as follows; the system created the bounding

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SHD360: A Benchmark Dataset for Salient Human

24/05/2021 Salient human detection (SHD) in dynamic 360° immersive videos is of great importance for various applications such as robotics, inter-human and human-object interaction in augmented reality. However, 360° video SHD has been seldom discussed in the computer vision community due to a lack of datasets with large-scale omnidirectional videos and rich annotations. To this end, we propose

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Salient human detection for robot vision Pattern

In this paper, we propose a salient human detection method that uses pre-attentive features and a support vector machine (SVM) for robot vision. From three pre-attentive features (color, luminance

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SHD360: A Benchmark Dataset for Salient Human

24/05/2021 24/05/2021 Salient human detection (SHD) in dynamic 360° immersive videos is of great importance for various applications such as robotics, inter-human and human-object interaction in augmented reality. However, 360° video SHD has been seldom discussed in the computer vision community due to a lack of datasets with large-scale omnidirectional videos and rich annotations. To

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What is Saliency Detection and how is it measured?

Scientists have made attempts at modelling human attention and saliency in computerised form. So far, they have not been able to mimic real- time performance. Accurate saliency detection in computerised form may have applications for photography, automatic image resizing and person identification. Issues with artificially modelling saliency detection include the fact that current models use

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Salient human detection for robot vision SpringerLink

30/03/2007 Salient human detection. Although most human detection systems can detect people, they can distinguish which humans appear more salient. However, the purpose of our work was to develops a salient human detection system for indoor environments. First, the steps for detecting salient objects proceeded as follows; the system created the bounding

get price

Salient human detection for robot vision — Yonsei University

In this paper, we propose a salient human detection method that uses pre-attentive features and a support vector machine (SVM) for robot vision. From three pre-attentive features (color, luminance and motion), we extracted three feature maps and combined them as a salience map. By using these features, we estimated a given object's location without pre-assumptions or semi-automatic interaction

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SHD360: A Benchmark Dataset for Salient Human Detection in

24/05/2021 24/05/2021 Salient human detection (SHD) in dynamic 360° immersive videos is of great importance for various applications such as robotics, inter-human and human-object interaction in augmented reality. However, 360° video SHD has been seldom discussed in the computer vision community due to a lack of datasets with large-scale omnidirectional videos and rich annotations. To

get price

Salient human detection for robot vision Pattern

In this paper, we propose a salient human detection method that uses pre-attentive features and a support vector machine (SVM) for robot vision. From three pre-attentive features (color, luminance

get price

SHD360: A Benchmark Dataset for Salient Human Detection in

24/05/2021 24/05/2021 Salient human detection (SHD) in dynamic 360° immersive videos is of great importance for various applications such as robotics, inter-human and human-object interaction in augmented reality. However, 360° video SHD has been seldom discussed in the computer vision community due to a lack of datasets with large-scale omnidirectional videos and rich annotations. To

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Using Machines to Improve Human Saliency Detection

Using Machines to Improve Human Saliency Detection unsupervised clustering and outlier detection to find salient regions. Most outlier detection schemes detect point outliers in the data, but we are interested in finding an outlier cluster: data that is an essential part of the image, and is thus not an outlier in the true sense of the word. Related work was reported by [11], wherein the

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Human Action Recognition using Salient Region Detection in

We suppress the false detection interest points by detecting salient regions. Furthermore, we encode the features according to their spatio-temporal relationship. Our method is verified on two challenging databases (UCF sports and YouTube), and the experimental results demonstrate that our method achieves better results than previous methods in human action recognition.

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Human action recognition with salient trajectories

01/11/2013 In Section 4, the recognition of human actions with salient trajectories is detailed. the proposed salient-C achieves superior results over other methods except that of the improved spatio-temporal feature detection . And with splits, salient-C outperforms all the other methods. Although Sadanand and Corso has achieved better results on this dataset, their approach involves a manual

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Inferring Salient Objects from Human Fixations

The fixation map, derived at the upper network layers, mimics human visual attention mechanisms and captures a high-level understanding of the scene from a global view. Salient object detection is then viewed as fine-grained object-level saliency segmentation and is progressively optimized with the guidance of the fixation map in a top-down

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Salience (neuroscience)

Saliency detection is often studied in the context of the visual system, but similar mechanisms operate in other sensory systems. Just what is salient can be influenced by training: for example, for human subjects particular letters can become salient by training. There can be a sequence of necessary events, each of which has to be salient, in turn, in order for successful training in the

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SHD360: A Benchmark Dataset for Salient Human Detection in

24/05/2021 Salient human detection (SHD) in dynamic 360° immersive videos is of great importance for various applications such as robotics, inter-human and human-object interaction in augmented reality. However, 360° video SHD has been seldom discussed in the computer vision community due to a lack of datasets with large-scale omnidirectional videos and rich annotations. To this end, we propose

get price

Salient human detection for robot vision Pattern

In this paper, we propose a salient human detection method that uses pre-attentive features and a support vector machine (SVM) for robot vision. From three pre-attentive features (color, luminance

get price

SHD360: A Benchmark Dataset for Salient Human Detection in

Salient human detection (SHD) in dynamic 360° immersive videos is of great importance for various applications such as robotics, inter-human and humanobject interaction in augmented reality. However, 360° video SHD has been seldom discussed in the computer vision community due to a lack of datasets with large-scale omnidirectional videos and rich annotations.

get price

GitHub PanoAsh/SHD360

02/08/2021 Salient human detection (SHD) in dynamic 360° immersive videos is of great importance for various applications such as robotics, inter-human and human-object interaction in augmented reality. However, 360° video SHD has been seldom discussed in the computer vision community due to a lack of datasets with large-scale omnidirectional videos and rich annotations. To this end, we propose

get price

Salience (neuroscience)

Saliency detection is often studied in the context of the visual system, but similar mechanisms operate in other sensory systems. Just what is salient can be influenced by training: for example, for human subjects particular letters can become salient by training. There can be a sequence of necessary events, each of which has to be salient, in turn, in order for successful training in the

get price

Inferring Salient Objects from Human Fixations IEEE

18/03/2019 Inferring Salient Objects from Human Fixations Salient object detection is then viewed as fine-grained object-level saliency segmentation and is progressively optimized with the guidance of the fixation map in a top-down manner. ASNet is based on a hierarchy of convLSTMs that offers an efficient recurrent mechanism to sequentially refine the saliency features over multiple steps. Several

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Few-Cost Salient Object Detection with Adversarial-Paced

salient object detection model based on the manual annotation on a few training images only, thus dramatically alleviating human labor in training models. To this end, we name this task as the few-cost salient object detection and propose an adversarial-paced learning (APL)-based framework to facilitate the few-cost learning scenario. Essentially, APL is derived from the self-paced learning

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Entropy Free Full-Text Salient Object Detection

Detection and localization of regions of images that attract immediate human visual attention is currently an intensive area of research in computer vision. The capability of automatic identification and segmentation of such salient image regions has immediate consequences for applications in the field of computer vision, computer graphics, and multimedia.

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RGB-D图像的显著性目标提取-论文解读 知乎

Salient object detection, which simulates human visual perception in locating the most significant object(s) in a scene, has been widely applied to various computer vision tasks. Now, the advent of depth sensors means that depth maps can easily be captured; this additional spatial information can boost the performance of salient object detection. Although various RGB-D based salient object

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论文阅读:Deeply Supervised Salient Object Detection with Short

13/03/2020 基于HED的改进. 在实验中,观察到更深的层可以更好地定位最显著的区域,因此基于HED的架构,将另一个侧输出连接到VGGNet中的最后一个池化层。. 此外,由于显著目标检测比边缘检测更困难,在每侧输出中添加了另外两个具有不同滤波通道和空间大小的卷积层

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