Emotion Detection Algorithm Player

Added on - Oct 2019

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Emotion Detection Algorithm Player
Table of ContentsIntroduction and overview...........................................................................................................................2Progress to date............................................................................................................................................3SVM:........................................................................................................................................................3Performance:............................................................................................................................................3Edge detection:........................................................................................................................................4Problems:.................................................................................................................................................4Performance:............................................................................................................................................5Face detection:.........................................................................................................................................5Problems:.................................................................................................................................................5Performance:............................................................................................................................................6Planned work...............................................................................................................................................6Steps in SVM:..........................................................................................................................................6Steps in edge detection:...........................................................................................................................7Steps in face detection:............................................................................................................................7Conclusion and Recommendations..............................................................................................................8Bibliography................................................................................................................................................9Appendices:...............................................................................................................................................111
Introduction and overviewMusic is an important part of the entertainment. Manual work is optimized and it gains huge attentionfor technological advancement. At present, there are various traditional music players, which select andorganize the songs manually. User needs to create and modify the play-list according to his mood. It is atime-consuming process. Some music players have included advanced features such as lyrics andrecommendation according to the preferred genre or singer. The user enjoys some of the features, andthere is room for improving the automation field in case of music players. Selection of songsautomatically and the arrangement depends on the user’s mood for a better experience (Kabaniet al.,2015). This is accomplished in the system that reacts to the user’s emotions, saves time that is spent inentering data manually.Emotions are expressed by facial expressions, gestures, speech etc. The system understands the user’smood from his facial expression. The system is capable of capturing facial expression by utilizing thedevice’s camera. There are several emotion recognition systems, which takes image, speech etc. as inputfor determining the emotion. The different approaches used in image processing edge detection are theemotional mouse, magic pointing, SUITOR, AI speech reorganising. Emotion mouse obtains theemotional condition like the heart beat, temperature etc. and obtains physiological data with the use ofdifferent sensors. A webcam is used in the magic pointing for determining the pupils of the user underrealistic as well as variable lightning conditions (Bhardwajet al.,2015). In the case of AI SpeechReorganition, the user uses the microphone for speaking to a computer and this speech is filtered andstored it in the RAM. When the user makes eye contact with the SUITOR, the device gets active and canautomatically detect his interest.The algorithms chosen for detecting emotions are Image Processing Edge Detection Algorithmimproved by Canny Operator, and Rapid Object Detection improved by Viola and Jones. In the edgedetection algorithm, an improved canny detection algorithm is introduced since the traditional algorithmfaced difficulties in treating images. An approach is introduced for minimizing the computation time andachieving high accuracy in the Object detection or Face detection algorithm (Senet al.,2018). Theapproach creates a face detection system that is 15 times faster as compared to the previous approach.The proposed system depends on the Blue Eyes technology that relates to emotion sensory environmentwhile the traditional authentication systems used the fingerprints, iris image and thumbprints. There are2
various techniques proposed for identifying emotional state and refers to facial affect program forspecifying the relationships between facial movements and specific emotions. The system includes aninterface for determining human gestures and facial emotions.Application:The media player automatically plays song according to the user’s emotions, acts as awebsite plug-in, recommends for YouTube, act as a personal assistant etc.Hardware and Software Requirements:The hardware requirements for the project include 4GB RAM,Intel i3, Speaker and Webcam. Software requirements include Python 2.7 and Open CV 3.1.Functional and Non-functional Requirements:Functional requirements are service statement providedby the system, and it deals with the system reaction to certain inputs. It identifies and learns the imagecaptured by the webcam. Machine learning supports vector classification with the help of a vectormachine. Non-functional requirements include the constraints and system properties that arise frombudget constraints, external factors like privacy registrations, organizational policies and user needs.Progress to dateSVM:SVM or support vector machines are supervised models that associate with machine learning algorithmsfor analyzing the data used in regression analysis. An SVM algorithm creates a model for assigning newexamples to a particular category or other, makes it a linear classifier.Performance:An SVM model represents examples in such a way that it becomes easy to divide theexamples into separate categories. An SVM constructs a hyper-plane of a hyper-plane set in high-dimensional space that is used for regression analysis or classification. The hyper-lane having the largestdistance to training data achieve a good separation since with the increase in the margin there is areduction in generalization error (Dinget al.,2015). A webcam streams real-time image through acomputer or a computer network. The video stream is saved viewed and shared to other networksthrough the systems like the email attachment and internet.3
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