How to detect if a person is interacting (as in touching) some object in an image? The 2019 Stack Overflow Developer Survey Results Are InState of the art for Object detection/image recognitionCNNs for identifying scattered object?Multiple Object recognition in image using deep LearningPerform Person Re-Identification on custom image setHow to label “other” while labeling image for object detection/classification?implement Sliding Window to detect text in an imageSimple Object DetectionDetect presence of text in imagemAP mean average precision for 4 object per image . Can you explain it?How to use mAP for 3 object on image
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How to detect if a person is interacting (as in touching) some object in an image?
The 2019 Stack Overflow Developer Survey Results Are InState of the art for Object detection/image recognitionCNNs for identifying scattered object?Multiple Object recognition in image using deep LearningPerform Person Re-Identification on custom image setHow to label “other” while labeling image for object detection/classification?implement Sliding Window to detect text in an imageSimple Object DetectionDetect presence of text in imagemAP mean average precision for 4 object per image . Can you explain it?How to use mAP for 3 object on image
$begingroup$
I am currently working on a human interaction problem, which tries to identify if a person touched a predefined object.
Current Approach: I am using open-pose to estimate the pose of the person then manipulating the keypoints returned into some logic (simple if else statements) which tells whether person interacted or not. However it seems to be a dirty workaround to me and is not a full proof solution. So is there any better approach I can go for?
Is there any predefined model or white paper I can refer for this problem?
I am struggling on how to detect the pose of a person in an image? Is there a way to classify the pose of a person in three categories like front, back and side?
machine-learning deep-learning
asked Oct 12 '18 at 10:56
Rachit TayalRachit Tayal
1032
$endgroup$
bumped to the homepage by Community♦ 30 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I am currently working on a human interaction problem, which tries to identify if a person touched a predefined object.
Current Approach: I am using open-pose to estimate the pose of the person then manipulating the keypoints returned into some logic (simple if else statements) which tells whether person interacted or not. However it seems to be a dirty workaround to me and is not a full proof solution. So is there any better approach I can go for?
Is there any predefined model or white paper I can refer for this problem?
I am struggling on how to detect the pose of a person in an image? Is there a way to classify the pose of a person in three categories like front, back and side?
machine-learning deep-learning
asked Oct 12 '18 at 10:56
Rachit TayalRachit Tayal
1032
$endgroup$
bumped to the homepage by Community♦ 30 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I am currently working on a human interaction problem, which tries to identify if a person touched a predefined object.
Current Approach: I am using open-pose to estimate the pose of the person then manipulating the keypoints returned into some logic (simple if else statements) which tells whether person interacted or not. However it seems to be a dirty workaround to me and is not a full proof solution. So is there any better approach I can go for?
Is there any predefined model or white paper I can refer for this problem?
I am struggling on how to detect the pose of a person in an image? Is there a way to classify the pose of a person in three categories like front, back and side?
machine-learning deep-learning
asked Oct 12 '18 at 10:56
Rachit TayalRachit Tayal
1032
$endgroup$
I am currently working on a human interaction problem, which tries to identify if a person touched a predefined object.
Current Approach: I am using open-pose to estimate the pose of the person then manipulating the keypoints returned into some logic (simple if else statements) which tells whether person interacted or not. However it seems to be a dirty workaround to me and is not a full proof solution. So is there any better approach I can go for?
Is there any predefined model or white paper I can refer for this problem?
I am struggling on how to detect the pose of a person in an image? Is there a way to classify the pose of a person in three categories like front, back and side?
machine-learning deep-learning
machine-learning deep-learning
asked Oct 12 '18 at 10:56
Rachit TayalRachit Tayal
1032
asked Oct 12 '18 at 10:56
Rachit TayalRachit Tayal
1032
asked Oct 12 '18 at 10:56
Rachit TayalRachit Tayal
1032
asked Oct 12 '18 at 10:56
Rachit TayalRachit Tayal
1032
asked Oct 12 '18 at 10:56
Rachit TayalRachit Tayal
1032
1032
bumped to the homepage by Community♦ 30 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 30 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
add a comment |
1 Answer
1
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oldest
votes
$begingroup$
There are papers that show how to estimate different poses. For example this one gives an overview of different methods: PoseTrack: A Benchmark for Human Pose Estimation and Tracking. You can take this benchmark and group all the poses into needed categories. For example, by manually assigning your groups. And then you use the categorization of poses like in paper and convert to the poses you need.
One of the solutions for pose tracking is Mask R-CNN. It uses a neural network with convolutional layers and predicts in parallel class, box and binary mask. Here is the original Mask R-CNN paper. And here is the ProTracker algorithm that achieved one of the best results on PoseTrack.
answered Oct 12 '18 at 20:58
keiv.flykeiv.fly
607110
$endgroup$
add a comment |
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$begingroup$
There are papers that show how to estimate different poses. For example this one gives an overview of different methods: PoseTrack: A Benchmark for Human Pose Estimation and Tracking. You can take this benchmark and group all the poses into needed categories. For example, by manually assigning your groups. And then you use the categorization of poses like in paper and convert to the poses you need.
One of the solutions for pose tracking is Mask R-CNN. It uses a neural network with convolutional layers and predicts in parallel class, box and binary mask. Here is the original Mask R-CNN paper. And here is the ProTracker algorithm that achieved one of the best results on PoseTrack.
answered Oct 12 '18 at 20:58
keiv.flykeiv.fly
607110
$endgroup$
add a comment |
$begingroup$
There are papers that show how to estimate different poses. For example this one gives an overview of different methods: PoseTrack: A Benchmark for Human Pose Estimation and Tracking. You can take this benchmark and group all the poses into needed categories. For example, by manually assigning your groups. And then you use the categorization of poses like in paper and convert to the poses you need.
One of the solutions for pose tracking is Mask R-CNN. It uses a neural network with convolutional layers and predicts in parallel class, box and binary mask. Here is the original Mask R-CNN paper. And here is the ProTracker algorithm that achieved one of the best results on PoseTrack.
answered Oct 12 '18 at 20:58
keiv.flykeiv.fly
607110
$endgroup$
add a comment |
$begingroup$
There are papers that show how to estimate different poses. For example this one gives an overview of different methods: PoseTrack: A Benchmark for Human Pose Estimation and Tracking. You can take this benchmark and group all the poses into needed categories. For example, by manually assigning your groups. And then you use the categorization of poses like in paper and convert to the poses you need.
One of the solutions for pose tracking is Mask R-CNN. It uses a neural network with convolutional layers and predicts in parallel class, box and binary mask. Here is the original Mask R-CNN paper. And here is the ProTracker algorithm that achieved one of the best results on PoseTrack.
answered Oct 12 '18 at 20:58
keiv.flykeiv.fly
607110
$endgroup$
There are papers that show how to estimate different poses. For example this one gives an overview of different methods: PoseTrack: A Benchmark for Human Pose Estimation and Tracking. You can take this benchmark and group all the poses into needed categories. For example, by manually assigning your groups. And then you use the categorization of poses like in paper and convert to the poses you need.
One of the solutions for pose tracking is Mask R-CNN. It uses a neural network with convolutional layers and predicts in parallel class, box and binary mask. Here is the original Mask R-CNN paper. And here is the ProTracker algorithm that achieved one of the best results on PoseTrack.
answered Oct 12 '18 at 20:58
keiv.flykeiv.fly
607110
answered Oct 12 '18 at 20:58
keiv.flykeiv.fly
607110
answered Oct 12 '18 at 20:58
keiv.flykeiv.fly
607110
answered Oct 12 '18 at 20:58
keiv.flykeiv.fly
607110
607110
add a comment |
add a comment |
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