Questions tagged [computer-vision]

For questions related to computer vision, which is an interdisciplinary scientific field (which can e.g. use image processing techniques) that deals with how computers can be made to gain high-level understanding from digital images or videos. For example, image recognition (that is, the identification of the type of objects in an image) is a computer vision problem.

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88 views

How to recognize sequence of digits in an image

I am learning to program neural networks and others, and I would like to know how I can get the numbers that are in an image, for example, if I pass an image that has 123 written, get with my model ...
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2answers
49 views

Should I use U-net to label keys in a keyboard image?

This is a 600*800 image. Which algorithm/model should I use to get an image like the one below, in which each key is detected and labeled by a rectangle? I guess this is some kind of a segmentation ...
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472 views

Algorithms for scene rotation

My goal is to take an image and return another image that looks as if the scene was viewed from another angle. The difference in angle can be small — let's say as if the hand holding the camera moved ...
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1answer
71 views

Extracting Descriptors and feature points for 3d mesh

I'm programming my work with python, and I have a mesh and I want to extract 3d descriptors and feature points from it( trying to work on multi-scale strategy) , to visualize them later on the mesh, ...
2
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1answer
46 views

Viola-Jones algorithm: Haar-like features, how are the features extracted?

If I have an image like this 1 2 3 4 5 6 7 8 a b c d e f g h ... And I apply a Haar-like feature with a template ...
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1answer
1k views

Are information processing rules from Gestalt psychology still used in computer vision today?

Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware ...
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38 views

Is it likely that a sentient AI experience synesthesia?

The reason I ask this question is because we humans tend to compartmentalize our sensory inputs, except in some individuals that experience synesthesia. If an Artificial Intelligence Entity (AIE) can ...
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16 views

Mixed precision training - why we're fine with doing point wise operations in FP32

I'm starting to learn more about mixed-precision training, and I'm in particular confused about point-wise operations. In the original article (link), the authors mention, citing: Point-wise ...
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28 views

Resources for Computer Vision Algorithms and Applications

Are there any videos or other books/notes/slides that anyone has come across that follow Computer Vision Algorithms and Applications by Richard Szeliski? We are using this book in class but the ...
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28 views

Can I use the SIFT feature detector on data other than images?

I know how to use SIFT algorithm for images but I never use it for other kinds of data. I have tabular data (x, y, z, time) where x,y,z is the joint position along x, y, z coordinates. Now, can I ...
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How can I improve the robustness of my Fire Detection algorithm in openCV?

I am working on a project to detect fire in CCTV or any other surveillance cameras. Up till now I have completed the following stages; Convert the RGB into HSV Sliced out the Value matrix from HSV ...
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2answers
629 views

How to use a VAE to reconstruct an image starting from an initial image instead of starting from a random vector?

Is it possible to use a VAE to reconstruct an image starting from an initial image instead of using K.random_normal, as shown in the “sampling” function of this ...
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What model structure I should use to train on low res and blurry images?

I am looking for advice or suggestion. I have photos like these: photo_1 and photo_2 and many more similar to that. The average shape of these photos is about 160 x 100. What we are doing is we are ...
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1answer
61 views

Should one use an "other" category in image classification?

In image classification, there are sometimes images that do not fit in any category. For example, if I build a CNN in Keras to classify Dogs and Cats, does it help (in terms of training time and ...
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10 views

Is there any method that combines temporal action proposals with multiple actions' classifiers?

I am trying to classify actions in untrimmed videos. These videos contain a very imbalanced set of actions (where the background class is the majority). I have previously tried frame-wise action ...
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23 views

What is the current approach to topological map building in robotics?

What is the current approach to topological map building in robotics? I suspect topological maps may be the correct approach to robot navigation vs rigid body SLAM, but most of the papers about ...
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1answer
47 views

Face recognition from single image provided

I am working on a computer vision project, based on face detection to record the time spent by a person in an office. It consists of detecting the face by camera number 1 (input), temporarily storing ...
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95 views

What are the main differences between YOLOv3 and RetinaNet object detection algorithms?

I am looking at a certain project that compares performance on a certain dataset for an object detection problem using YOLOv3 and RetinaNet (or the "SSD_ResNet50_FPN" from TF Model Zoo). ...
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34 views

Are there any faster and more efficient object tracking algorithms other than DeepSORT and centroid tracker?

Recently, I am trying some algorithm for object tracking, such as DeepSORT and centroid tracker. However, these trackers are slow to run on mobile devices, or even on a single-GPU laptop. Does anyone ...
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1answer
40 views

How does YOLO handle non-class objects?

I have been reading more about computer vision and I'm bothered by YOLO and similar deep learning architectures. The thing I am confused about is how non-class image sections are dealt with. In ...
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0answers
27 views

What are the metrics to be used for unsupervised monocular depth estimation in computer vision?

I am currently replicating the results of this paper. In this paper they have not mentioned how they are evaluating the results as no ground truth is available for comparison. Same goes for other ...
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1answer
24 views

Is there a methodology for splitting up annotated orthophotos into smaller photos that retain the original bounding boxes?

I'm trying to train an object detection algorithm (i.e. YOLOv4 Scaled, Faster R-CNN) on data taken from large orthophotos. Let's say I have one class, and I label the entire orthophoto with bounding ...
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9answers
6k views

How is it possible that deep neural networks are so easily fooled?

The following page/study demonstrates that the deep neural networks are easily fooled by giving high confidence predictions for unrecognisable images, e.g. How this is possible? Can you please ...
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Object detection approaches without anchors and NMS

The Context From all of the problems I have worked with in computer vision, the most challenging one is the object detection. This is not because the problem itself is complex to understand or bad ...
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19 views

How to augment 2.5D keypoints?

I am currently working on 3D hand pose estimation. The idea is to first detect the 2.5D pose representation and then obtain 3D pose with the help of camera parameters. For some reason, I was trying to ...
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0answers
36 views

CNN leaf segmentation throught classification of edges how to improve

I am trying to design a CNN that can do pixel wise segmentation of edges leaves in dense foliage agriculture images. Such as these: On the basis of this article https://arxiv.org/pdf/1904.03124.pdf, ...
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1answer
81 views

How do you calculate KL divergence on a three-dimensional space for a Variational Autoencoder?

I'm trying to implement a variational auto-encoder (as seen in Section 3.1 here: https://arxiv.org/pdf/2004.06271.pdf). It differs from a traditional VAE because it encodes its input images to three-...
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23 views

Which F1-score is used for the semantic segmentation tasks?

I read some papers about state-of-the-art semantic segmentation models and in all of them, authors use for comparison F1-score metric, but they did not write whether they use the "micro" or &...
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1answer
68 views

How to treat (label and process) edge case inputs in machine learning?

In every computer vision project, I struggle with labeling guidelines for border cases. Benchmark datasets don't have this problem, because they are 'cleaned', but in real life unsure cases often ...
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1answer
108 views

How does the region proposal method work in Fast R-CNN?

I read so many articles and the Fast R-CNN paper, but I'm still confused about how the region proposal method works in Fast R-CNN. As you can see in the image below, they say they used a proposal ...
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0answers
34 views

How does the region proposal algorithm in R-CNN work? [duplicate]

I'm trying to understand R-CNN, but I'm a bit lost in the first stage (region proposal). Correct me if I'm wrong, but as far as I understand, there is an algorithm that proposes regions in the image ...
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36 views

Time series analysis using computer vision principles

I'm just starting to explore topics within computer vision and curious if there are any concepts in that area that could be applied to segmenting multivariate time series with the goal of grouping ...
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28 views

How are Ground truth provided to each Pyramid map in RetinaNet or YOLOv3 Paper? How is the mapping of Feature Pyramids done to Ground Truth

SO the YOLO V3 and RetinaNet both uses the Feature pyramids which look something like this: (except b and e which have one ...
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35 views

How does the embeddings work in vision transformer from paper?

I get the part from the paper where the image is split into P say 16x16 (smaller images) patches and then you have to ...
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2answers
672 views

How to architect a network to find bounding boxes in simple images?

I have an application where I want to find the locations of objects on a simple, relatively constant background (fixed camera angle, etc). For investigative purposes, I've created a test dataset that ...
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2answers
3k views

Is it possible to run SSD or YOLO object detection on Raspberry Pi 3 for live object detection?

Is it possible to run SSD or YOLO object detection on Raspberry Pi 3 for live object detection (2/4frames x second)? I've tried this SSD implementation but it takes 14 s per frame. Is there anything I ...
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1answer
2k views

How can I detect thin objects (like pens and pencils) without a bounding box but only 2 endpoints and the orientation?

I am looking to detect thin objects, like pens, pencils, and surgical instruments. The bounding box is not important, but I am looking to see if I can train a model to detect both the object as well ...
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1answer
1k views

Can YOLO detect large objects?

I have a rather basic question about YOLO for bounding box detection. My understanding is that it effectively associates each anchor box to an 8-dimension output. During testing, does YOLO take each ...
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3answers
10k views

Is it difficult to learn the rotated bounding box for a (rotated) object?

I have checked out many methods and papers, like YOLO, SSD, etc., with good results in detecting a rectangular box around an object, However, I could not find any paper that shows a method that learns ...
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0answers
50 views

Can I use a CNN for template matching, so that there is robustness, as the background of the target image is not that good?

I have to extract part of a source image, then I have to check if it is similar or almost similar to any of the 10 target images, so that I can do further processing on that one specific target image, ...
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1answer
795 views

How to label training data for YOLO

I am having a question on how to label training data for YOLO algorithm. Let's say that each label Y, we need to specify $[P_c, b_x, b_y, b_h, b_w]$, where $P_c$ is the indicator for presence (1=...
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1answer
578 views

How are IOUs for ground truth boxes in YOLO calculated?

I know how IOU works during detection. However, while preparing targets from ground-truth for training, how is the IOU between a given object and all anchor boxes calculated? Is the ground truth ...
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1answer
3k views

In YOLO, what exactly do the values associated with each anchor box represent?

I'm going through Andrew NG's course, which talks about YOLO, but he doesn't go into the implementation details of anchor boxes. After having looked through the code, each anchor box is represented by ...
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0answers
25 views

Where can I find a progressively trained GAN's pretrained low-resolution models?

StyleGAN is trained progressively, meaning that it starts as a small network trained to produce 4x4 images, then a layer is added which doubles the resolution to 8x8, then 16x16, etc. The final result ...
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0answers
10 views

How to predict multiple set of coordinates (of bounding boxes) for signboards text localization through neural network?

I am creating a signboard translation application from scratch. I have images of signboards where there are multiple texts and I have the corresponding set of coordinates of bounding boxes for ...
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1answer
225 views

Why does nobody use decision trees for visual question answering?

I'm starting a project that will involve computer vision, visual question answering, and explainability. I am currently choosing what type of algorithm to use for my classifier - a neural network or a ...
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1answer
71 views

What does the Fourier transformed image mean?

I have been trying to figure out what the Fourier transformed image represents. I am aware of Fourier transformation in general, but I can't explain myself the image it forms after transformation. ...
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0answers
18 views

Nonrealtime tracking for object detection (with or without deep features)

I've been doing a search for tracking systems based on bounding box for several days (like Sort, DeepSort, Motpy, ...). But neither is nonrealtime. My problem is based on the tracking of multiple ...
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0answers
31 views

Does the selective search algorithm in object detection learn?

I am trying to get a better grasp of how object detection works. I (almost) completely understand the concept behind RPNs. However, I am a little bit confused with the selective search algorithm part. ...
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0answers
12 views

How are the parameters $\alpha_i$ of hard attention trained?

I have a question about Show, Attend and Tell: Neural Image CaptionGeneration with Visual Attention paper by Xu. The basic mechanism of stochastic hard attention is that each pixel of the input image ...

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