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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1answer
823 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 ...
4
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0answers
22 views

Extending FaceNet’s triplet loss to object recognition

FaceNet uses a novel loss metric (triplet loss) to train a model to output embeddings (128-D from the paper) such that any two faces of the same identity will have a small Euclidean distance, and such ...
4
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0answers
19 views

Video summarization similar to Summe's TextRank

We have the popular TextRank API which given a text, ranks keywords and can apply summarization given a predefined text length. I am wondering if there is a similar tool for video summarization. ...
4
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1answer
191 views

Other Deep Learning Networks for Visual Place Recognition?

I am doing a project on Visual Place Recognition in Changing Environments. The CNN used here is mostly AlexNet, and a feature vector is constructed from Layer 3. Does anyone know of similar work ...
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0answers
38 views

How do I denoize a microscopic image?

I'm working in a computer vision project, where the goal is to detect some specific parasites, but now that I have the images, I noticed that they have a watermark that specifies the microscope ...
3
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0answers
82 views

YOLO v3 complete architecture

I am attempting to implement YOLO v3 in Tensorflow-Keras from scratch, with the aim of training my own model on a custom dataset. By that, I mean without using pretrained weights. I have gone through ...
3
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1answer
245 views

Alternative to sliding window neural network (was: Object detect (or) image classification at specific locations in the frame)

Recent advances in Deeplearning and dedicated hardware has made it possible to detect images with a much better accuracy than ever. Neural networks are the gold standard for computer vision ...
3
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2answers
203 views

Point A to B Avoidance

I understand A* and Dijkstra for avoiding obstacles, they require that points are traversable there are points that are not traversable thus the algorithms wont bump into the obstacles because the ...
2
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0answers
19 views

Confidence Maps and Non-Linearity

I am currently trying to improve a CNN architecture that was proposed for generating depth images. The architecture was originally proposed for autonomous driving and it looks like following : The ...
2
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0answers
18 views

How can I detect fast and slow motion in videos?

I'm trying to detect if a given video shot is fast or slow motion. Basically, I need to calculate a "video motion" score in a given video sequence, meaning how fast or slow motion the video is. For ...
2
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0answers
15 views

Reverse engineering controller sensitivity/aim for several games ie acceleration curves, deadzones, etc

A machine learning project I am working on requires me to interface with an Xbox controller connected to a PC. The implementation must do the following two things: Record the joystick input from the ...
2
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0answers
38 views

Does Retina-net's focal loss accomplish its goal?

Taking out the weighting factor we can define focal loss as $$FL(p) = -(1-p)^\gamma log(p) $$ Where $p$ is the target probability. The idea being that single stage object detectors have a huge ...
2
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0answers
20 views

Estimate distance between points in perspective image

I am trying to estimate the real world distance (in metres) between two points in a perspective image using an uncalibrated camera. However, the dimensions of an object in the image are known. I ...
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0answers
24 views

Calculating tangent vector of curve s(P,$\alpha$) at given point $\alpha$ = 0

I am reading the paper "Transformation Invariance in Pattern Recognition – Tangent Distance and Tangent Propagation", where the tangent vector is calculated for the given curve $s(P,\alpha)$ at $\...
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0answers
29 views

Presence of object (highly occluded vehicle) in a scene

How to detect presence of object (highly occluded) in a scene? There are specific features (small patterns, etc), which allow to say that object is present, but it is not enough for detection for ...
2
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1answer
394 views

Neural Network for Optical Mark Recognition?

I've created a neural net using the ConvNetSharp library which has 3 fully connected hidden layers. The first having 35 neurons and the other two having 25 neurons each, each layer with a ReLU layer ...
2
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1answer
124 views

Which evaluation methods can I use for image segmentation?

I implemented an image segmentation pipeline and I trained it on the DICOM dataset. I compared the results of the model with manual segmentation to find the accuracy. Is there other methods for ...
2
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0answers
169 views

Extracting specific features using HOG

I am using HOG (Histogram of Oriented Gradients) for car detection from a video. I have used the Matlab function extractHOGFeatures() , it has given me a feature ...
2
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0answers
35 views

Detecting symmetry in small images with RNN

My network works on 32x32 normalized (translationally) but noisy images. Its task it to determine whether image has simple symmetry (horizontal/vertical). It needs to be reasonably robust to rotation (...
2
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0answers
53 views

How do cognitive services work?

Currently big tech companies like Microsoft, Google, and Amazon (to name a few) offer cognitive services on their cloud platforms. With these services it is possible to identify faces, objects, texts,...
2
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1answer
101 views

possible to train some model to recognize trash?

I want to build a semi autonomous robot/machine that will clean up trash in cities. For this to be possible it needs to recognize 'trash'. As trash can be all sorts of things (think ciggaret buts, ...
1
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1answer
14 views

What should load_mask() return if an image doesn't have any objects? (Mask RCNN)

I want to use Mask RCNN to do image segmentation. I need to override the load_mask function for the dataset class. I know this function should return mask tensors and class ids of objects in an image. ...
1
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0answers
24 views

How to implement fisherface algorithm and how much time will it take?

I found on the web that fisherface is the best algorithm for face detection. Before investing deeply into it, I just want to know how hard is it to implement it and how much time will it take. I am ...
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0answers
23 views

How do I generate structured light for the 3D bin picking system?

I want to know how to generate the structured light which projects different patterns of light on a 3D object which is under scanning.
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0answers
7 views

How to use machine learning to create combine of opposite images side by side

Inspired by: Two Worlds Pictures I just want to create a Machine Learning Model that can automatically combine the opposite images into 1 image. I am thinking about 2 possible solutions: Pose ...
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0answers
16 views

Can Microsoft's cognitive service find similar person in a set of images without using the face service?

I need to create an application that can detect if a person X entered as an input exists in an image set and return as output all the images in which the person X exists. The problem is that the ...
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0answers
10 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, ...
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0answers
11 views

Understanding average precision (AP) in measuring object detector performance

I am trying to understand the average precision (AP) metrics in evaluating the performance of deep-learning based object detection models. Suppose we have the following ground true (four objects ...
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0answers
34 views

Object size identification and maximum number of classes with convolutional neural networks

I am working on a project that involves using a ConvNet to identify screws. I am able to train from scratch a ConvNet based on the first version of the inception network, but shallower (only 3 ...
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0answers
31 views

Image-Specific Class Saliency Visualisation

In the paper "Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps", https://arxiv.org/abs/1312.6034, at part 3, there is a first-order Taylor expansion(...
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0answers
23 views

Live video object detection with pose estimation

I was researching about hierarchical object detection, and end up reading that Yolo v3 is the state of art for that kind of tasks, besides, the inference time make it one of the best for run it on ...
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0answers
68 views

Siamese Network for unknown object

I am currently trying to create a One-Shot network using the Siamese architecture for an object that isn't a face. My problem is, in normal Face Recognition the detecting gadget (e.g. Smartphone) ...
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0answers
28 views

Why is the learning rate is already very small (1e-05) while the model convergences too fast?

I am training a video prediction model. According to the loss plots, the model convergences very fast while the final loss is not small enough and the generation is not good. Actually, I have test ...
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0answers
83 views

Tensorflow : Inception V3 Transfer Learning Parameter Tuning

Sorry if my question is at the wrong place, I'm new in this community. So, I have dataset with total of 1 million images (augmented) that separated in 28 classes. I followed this tutorial https://www....
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1answer
71 views

Appropriateness of 3D Convolutional Neural Network for segmentation of medical image data

I have a couple different segmentation tasks that I would like to perform on medical imaging data using CNN's. I'm currently trying to wrap my head around how well a 3D network might work, using a U-...
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0answers
36 views

Image Segmentation Prediction with cropping 256x256 grids is very slow

I have only a limited dataset (<25) with large-sized images (>1500x2000) and their pixelwise labels. The aim is to find unusual patterns in this industry dataset and highlight them. To generate ...
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0answers
20 views

Is there any deep learning object detection algorithms that can work without bounding boxes annotated data?

For example Haar Cascade can be trained using only positive and negative examples, you don't need any bounding box annotations. But it not a deep learning approach. Another example can be the most ...
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0answers
19 views

How exactly is equivariance achieved in capsule networks?

I have read quite a lot about capsule networks but cannot understand how the squashed vector would also rotate in response to rotation or translation of the image.A simple example would be helpful.I ...
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0answers
18 views

input annotations quality check for large scale image data

while dealing with image data at very large scale, there are different sources where data is coming from. Often, we do not have any control over quality of labels/ annotations. I already do use ...
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0answers
21 views

Good papers for implementing as project of computer vision course

I'm a student of Artificial Intelligence. This semester I've Computer Vision course. We should select a topic related to intelligent vehicles and read several papers and implement one of those paper. ...
1
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1answer
83 views

How do I segment each part of a DICOM image?

As I'm beginner in image processing, I am having difficulty in segmenting all the parts in DICOM image. Currently, I'm applying watershed algorithm, but it segments only that part that has tumour. ...
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0answers
26 views

Difference in trained models between GCP's Google Vision and Firebase's ML kit?

Anyone here know if the image-recognition/text-recognition/etc features of Google Vision API use the same trained models as the image-recognition/text-recognition/etc of Firebase's ML kit? If they don'...
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0answers
40 views

How to combine heterogeneous image features extracted with different algorithms for similar image retrieval?

Say I have access to several pre-trained CNNs (e.g. AlexNet, VGG, GoogleLeNet, ResNet, DenseNet, etc.) which I can use to extract features from an image by saving the activations of some hidden layer ...
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0answers
24 views

Commercial API Q: is there an api for converting vision tags into a caption?

There are many machine learning api for scanning images but they just return a bunch of tags. https://azure.microsoft.com/en-gb/services/cognitive-services/computer-vision/ ...
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0answers
61 views

Data extraction from medical reports

I am new in Machine Learning. I have taken a course in vision and we are required to do a project. I am thinking of data mining medical lab report images. My code must take an image and jpg file ...
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0answers
40 views

Continuous ground truth in supervised (metric) learning?

I am writing my thesis in the field of (deep) metric learning (DML). I am training a network in the fashion of contrastive / triplet Siamese networks to learn similarity and dissimilarity of inputs. ...
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2answers
120 views

Neural Network that Predicts Game State Based on Actions

I am trying to find literature on a network architecture that takes the following as in input: Action (like 'Up', 'Down', etc) Image of current state and outputs: Image of next state I already ...
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0answers
8 views

Which metrics of COCO API are suitable for object detection

These days I train a person detector and I use COCO API to evaluate my model. It uses Recall and Precision to evaluate a detection task. It's output is something like this: ...
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0answers
14 views

How to recognize two different objects with the similar shape, but different size

I am using Mask-RCNN neural network. I retrained my network to detect and mask wheels of die-cast toy cars. I am using images, which present the side of the car (left or right). Sometimes the cars ...
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0answers
9 views

What is best dataset for person reidentification?

There are many datasets for person reidentification. I want to train a robust person re-identification neural network. Therefore I want to ask about best person re-identification dataset.