Questions tagged [object-recognition]

For questions related to object recognition, which is the problem of determining the type of object in the image, so object recognition could also be called object classification.

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19
votes
1answer
664 views

Would Google's self-driving-car stop when it sees somebody with a T-shirt with a stop sign printed on it?

In Hidden Obstacles for Google’s Self-Driving Cars article we can read that: Google’s cars can detect and respond to stop signs that aren’t on its map, a feature that was introduced to deal with ...
7
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2answers
5k views

Learning Rotated bounding box for object detection

I have checked out many methods and paper like yolo, ssd, etc with very promising result in detecting a rectangular box around object, But could not find any paper, which shows an learning a rotated ...
5
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2answers
72 views

Can translational invariance of CNNs be unwanted if object is likely in certain positions?

Various texts on using CNNs for object detection in images talk about how their translation invariance is a good thing. Which makes sense for tasks where the object could be anywhere in the image. Let'...
5
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1answer
262 views

What will happen when you place a fake speedsign on a highway?

I was wondering what will happen when somebody places a fake speedsign, of 10 miles per hour on a high way. Will a autonomous car slow down? Is this a current issue of autonomous cars?
5
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2answers
236 views

Can one use an Artificial Neural Network to determine the size of an object in a photograph?

My question relates to but doesn't duplicate a question that has been asked here. I've Googled a lot for an answer to the question: Can you find the dimensions of an object in a photo if you don't ...
5
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1answer
701 views

Precise localization and characterization of rudimentary shapes with neural networks

I understand that there are flavors of (convolutional) neural networks that are useful for object localization and detection tasks of reasonable difficulty. In all of the examples I have seen so far, ...
5
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2answers
61 views

How to know whether the object is moving after it is being detected?

If my algorithm detects the type of object, how should I know if that object is moving or not? Suppose a person carrying an umbrella. How to know that the umbrella is moving? I am working on a ...
5
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2answers
944 views

Are there any pretrained models for human recognition from all angles?

I need to be able to detect and track humans from all angles, especially above. There are, obviously, quite a few well-studied models for human detection and tracking, usually as part of general-...
5
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1answer
545 views

Understanding the loss function of You Only Look Once(YOLO) network

I'm trying to implement a custom version of YOLO neural network. Originally it was described in this paper. I have some problems understanding the loss function they used. Basic information: An ...
5
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1answer
169 views

What are the ways to calculate the error rate of a deep Convolutional Neural Network, when the network produces different results using the same data?

I am new to the object recognition community. Here I am asking about the broadly accepted ways to calculate the error rate of a deep CNN when the network produces different results using the same data....
5
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2answers
127 views

How data augmentation like rotation affects the quality of detection?

I'm using an object detection neural network and I employ data augmentation to increase a little my small dataset. More specifically I do rotation, translation, mirroring and rescaling. I notice that ...
4
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1answer
1k views

How to detect LEGO bricks by using a deep learning approach?

In my thesis I dealt with the question how a computer can recognize LEGO bricks. With multiple object detection, I chose a deep learning approach. I also looked at an existing training set of LEGO ...
4
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1answer
42 views

Are there methods that allow deep networks to learn object categorization in a self-supervised way?

When training a deep network to learn object classification from a set like ImageNet, we minimize the cross entropy between the ground truth and the predicted categories. This is done in a supervised ...
4
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1answer
795 views

Training a CNN from scratch over COCO dataset

I am using Tensorflow Object Detection API for training a CNN from scratch on COCO dataset. I need to use this specific configuration. There is no pre-trained model on COCO with that configuration and ...
4
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0answers
94 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 ...
3
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4answers
231 views

What could an oscillating training loss curve represent?

I tried to create a simple model that receives an $80 \times 130$ pixel image. I only had 35 images and 10 test images. I trained this model for a binary classification task. The architecture of the ...
3
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1answer
575 views

Regarding Yolo and Keras [closed]

I'm trying to implement YOLO (tiny version, v1) into Keras framework. For the past two days, I've been relentlessly digging through Github and the likes in order to ...
3
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1answer
82 views

Is there any computer vision technology that can detect any type of object?

Is there any computer vision technology that can detect any type of object? For example, there is a camera fixed, looking in one direction always looking at a similar background. If there is an object,...
3
votes
1answer
208 views

Why does the classifier network in RPN output two scores?

The region proposal network (RPN) in Faster-RCNN models contains a classifier and a regressor network. Why does the classifier network output two scores (object and background) for each anchor instead ...
3
votes
1answer
447 views

How does Google's self-driving car identify pedestrians?

Based on the article Google's self-driving cars can now spot cyclists: Sensors can read hand signals and predict rider's behaviour, Google's self-driving cars can spot cyclists, cars, road signs, ...
3
votes
1answer
947 views

What is the difference between 'Pixel' based object recognition and 'Feature' based object recognition?

From my understanding and text I found in research papers online : 1) Pixel based object recognition: Neural networks are trained to locate individual objects based directly on pixel data. 2) ...
3
votes
1answer
1k views

How to detect the empty parking spots?

I have some images of the empty parking as shown below. I 'd like to use deep learning to extract the parking spots. But in the beginning,am confused whether there are several ways to do the ...
3
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1answer
160 views

What are some techniques/method that can be used to train and detect objects like cars and humans?

I have used OpenCV to train Haar cascades to detect face and other patterns. However I later realized that Haar tends to give a lot of false positives and I learned of Hog would give a more accurate ...
3
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1answer
3k views

Identifying cars using deep learning

I would like to use deep leaning for identifying cars; I want the system to predict wether an object is a car or not. How can I do that knowing that im still a beginner in the Deep Learning field ? I ...
3
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0answers
208 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
votes
1answer
366 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 ...
2
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3answers
162 views

Small size datasets for object detection, segmentation and localization

I am looking for a small size dataset on which I can implement object detection, object segmentation and object localization. Can anyone suggest me a dataset less than 5GB? Or do I need to know ...
2
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3answers
110 views

What would the commercial application of a conscious AI look like/be?

Sometimes, but not always in the commercialization of technology, there are some low hanging fruits or early applications, I am having trouble coming up with examples of such applications as they ...
2
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1answer
62 views

Is it possible to train a CNN to predict the dimensions of primitive objects from point clouds?

Is it possible to train a convolutional neural network (CNN) to predict the dimensions of primitive objects such as (spheres, cylinders, cuboids, etc.) from point clouds? The input to the CNN will be ...
2
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1answer
34 views

Which API can I use for tracking the position of animal in one or more images?

I'd like to build an application for tracking the position of a given animal (e.g. a cat) in a series of images. Is there any off-the-shelf API I could use? Azure has some Vision APIs, but it seems ...
2
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2answers
67 views

Could AI understand what the number one is and detect it in our real world same as AI can recognize cars and other things?

I have a solid understanding what the numbers are. If I want, I can see numbers in everything. Could an AI have the same ability for any incoming information to tag them by numbers same as I have?
2
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1answer
31 views

Recognize carp and give them a unique id

For my internship assignment I have to implement a proof of concept for an application that is supposed to scan a picture with a carp on it and identify which carp this is. All of the carps that are ...
2
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1answer
90 views

Is there any other rotated object detection datasets?

I have googled for a long time for rotated object detection datasets. Most of papers focused on rotated object detection using DOTA, HRSC2016 or coco text detection dataset. Some researcher also ...
2
votes
2answers
637 views

Find object location (x, y) in an image

I am generating images that consist of points where the object's location is where the most overlap of points occurs. In this example, the object location is (25, 51). I am trying to train a model to ...
2
votes
2answers
1k views

What's the role of bounding boxes in object detection?

I'm quite new to the field of computer vision and was wondering what are the purposes of having the boundary boxes in object detection. Obviously, it shows where the detected object is, and using a ...
2
votes
1answer
123 views

Tracking object

At this moment, I am able to use NN to identify object such as human when given a frame from the camera. Once locate the object, then I can feed the human object image to either NN that's designed to ...
2
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1answer
107 views

Object detection doubt

I asked this question on /r/learnmachinelearning, but there was no answer so I'm reposting it here. I was reading this article on detecting rectangles in an image, here. My doubt is in the part where ...
2
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0answers
15 views

Detect object in video and augment another video on top of it

I'm trying to detect an object in a video (with slight camera movement), and then augment another video on top of it. What is the simplest approach to do that? For instance, let's assume I have this ...
2
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0answers
28 views

YOLO 9000 about Better Stronger

In this paper, YOLO has three features compared to YOLO v1. This question is about Better and Faster. In the Better section, there are many techniques such as Batch Norm, Anchor Box and so on. In the ...
2
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0answers
34 views

FasterRCNN's RPN network training

I would like to know if my understanding of RPN training is correct, and if never training the RPN on some specific anchor box is bad (i.e if the anchor never sees good nor bad examples). To make my ...
2
votes
1answer
56 views

Pose estimation using CNNs on Point clouds

In the case of single shot detection of point clouds, that is the point cloud of an object is taken only from one camera view without any registration. Can a Convolutional Network estimate the 6d pose ...
2
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0answers
98 views

Is there a dataset for the detection of bomb explosions?

I would like to train a deep neural network to recognize bomb explosions. I was wondering if there is an open visual dataset for bomb explosion? Alternatively, if you know a good deep architecture or ...
2
votes
0answers
17 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 ...
2
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0answers
45 views

How should I build an AI that quickly detects falling game assets on screen?

I want to build an AI that plays a simple android game. The game is just a one at a time object falling, some times at an angle. The AI needs to recognize the object and to decide whether to swipe ...
2
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0answers
38 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 ...
2
votes
0answers
25 views

Sails size recognition

Is it possible to recognize the height and width of the sails of different kitesurfers and windsurfers taken from public webcams? And show these information on video in real time? Or on screenshots?
2
votes
2answers
822 views

How do I detect similar objects in an image?

I want to tackle the problem of detecting similar objects in an image. To illustrate the problem consider this photo of some Lego bricks as my "input": The detection routine should identify similar ...
2
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0answers
32 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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0answers
44 views

How a game playing agent could identify potential objects and proximity?

Most implementations I'm seeing for playing games like Atari (usually similar to DeepMind's work using DQN) have 4 graphical frames of input fed into 3 convolutional layers which are then fed into a ...
2
votes
0answers
498 views

Getting worse performance when training a pre-trained model with the existing class

I am training pre-trained SSD-InceptionV2-Coco to detect the "car", which is one of the classes in mscoco label. I train the model with ~50k sample from KITTI, 500k iteration with batch size 2. I ...