Personality has a strong influence on people?s lives, behaviors, and decisions. So personality prediction has been an active field of research for a long time. However, due to the increase in computation power, there has been a growing interest in recognizing the human personality and integrating th
An automated personality prediction by video processing using deep learning
Personality has a strong influence on people’s lives, behaviors, and decisions. So personality prediction has been an active field of research for a long time. However, due to the increase in computation power, there has been a growing interest in recognizing the human personality and integrating them into computing, also known as “personality computing.”
Previously Predicting personality using traditional questionnaires was too time-consuming with a human error that cannot be disregarded and may produce biased decisions that may result in unreliable solutions.
The existing ML solutions are based on single features, which is inefficient or predicts higher accuracy results. So our system will use bimodal fusion to predict personality which is more accurate in comparison to previously proposed systems. The most outstanding thing about our project is that we will be generating our own dataset for Pakistani demography. This act allows us to achieve highly accurate results at a local level.
In our project, we are developing a hybrid mobile application that will run on both android and iOS. We are using Flutter to build an app. Our mobile application allows us to upload a short video to carry out predictions.
We are using deep learning algorithms such as convolutional neural network (CNN) and long short term memory (LSTM) to train our model. Our trained model will be connected to our app using Flask API.
Our objective for this FYP is that an automated personality analysis can be performed using a system by simply processing a video of 10 seconds. Moreover, it will include the development of a cross-platform application that detects the person's personality using video processing. Also, we will define and train facial, audio, ambiance, and transcript features models. To see the analysis we will combine results from all the above models using fusion. One of our most important objectives that are not achieved before is to create and upload a local dataset consisting of video interviews. We will gather data from our local hospitals and medical centers which will be labeled by a physiatrist who will be on board with us as we want to achieve accurate analysis which can be used in industry and other sectors of work. This will lead to the screening of candidates that a company is not looking for with some specific traits. One of our greatest objectives to achieve is that we will try to alter the phycology test that is conducted in our armed forces by trained professionals which consumes a lot of costs, time, and effort. This project will provide screening of non-eligible candidates that the armed forces are not looking for
Our project is a combination of two sciences i.e.
Psychology (the science of mind and behavior), and computer science.
Our project implementation is also based on two main models. The first model is the Rule-based model in which we have defined personality traits parallel to certain facial features and audios features.
The second model is the model in which automated personality analysis will be performed. Video analysis consists of a few steps. Firstly, some image processing techniques are applied to the sample video provided by the user to extract facial features. The next step is to extract audio features. After extracting features through segmentation, the classification is performed using deep learning models. In order to improve accuracy, the repetitiveness of traits is considered and the dominant trait is fetched.
The benefits of this project are in many sectors of work including human resources, political movements, media recommendations, forensics, health care, counseling, and many more as per user and with modifications.
One of the benefits is enhanced, personal assistants. Present-day automated voice assistants such as Siri, Google Assistant, Alexa, etc. can be made to automatically detect the personality of the user and, hence, give customized responses.
Other benefits include:
These are the benefits that can be seen directly but there are many more which can be utilized by modifying the analysis and using it in a different way.
We are developing a deep learning-based system that will predict a person's personality without human interference for that purpose we will train a model on audio and visual features and in the end combine them to get the personality of a person based on OCEAN. For audio, we will use LSTM and for visual features, we will use CNN as our model. After training our model we will deploy it on a server using flask (python micro web framework).and then design an app using flutter for accessing our model through it and getting our predictions.
Our APP will have three screens the first screen will be a splash Screen (usually represents the brand/company name). the second screen will be a Dashboard screen in which we have the option to move to other screens that will be Predict from the gallery, Record now, About Us, and user manual.
Our system will be only for the English language only initially. And require high-speed internet with a good camera on a user device to work efficiently. And generally, it will be compatible with devices with an android version greater than seven and iOS six.


| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Nividia GeForce GPU | Equipment | 1 | 40000 | 40000 |
| Smart Phone | Equipment | 1 | 20000 | 20000 |
| IP Camera | Equipment | 2 | 3700 | 7400 |
| Transport, Delivery and fuel | Miscellaneous | 1 | 5000 | 5000 |
| App Charges | Miscellaneous | 1 | 5000 | 5000 |
| Total in (Rs) | 77400 |
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