PENGENALAN AKTIVITAS MANUSIA DAN PEMBUATAN LOG OTOMATIS DARI REKAMAN VIDEO MENGGUNAKAN MULTILAYER PERCEPTRON
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Abstract
Advances in technology have made it easier to surveillance purpose by installing recording equipment that can be placed in certain strategic locations. The existence of this technology also brings changes in the analysis phase of video recordings and images that have been obtained. The processing of recorded videos no longer uses manual methods but can be done automatically using image processing and artificial intelligence algorithms. Based on the obtained video recordings, analysis can be carried out for surveillance purpose, object tracking, human activity recognition, etc. This paper discusses the development of an automatic human activity recognition system based on video recordings using Multilayer Perceptron method. The recorded video will be transformed into a collection of images which are then processed with the Multilayer Perceptron algorithm for the recognition process. The output of the designed system is the recognition of activities carried out by humans at a certain time and saved them in a log with a certain timestamp. In this paper, there are five types of human activities that can be recognized automatically by the system, namely raising hands, clapping, standing, sitting, and studying. The experimental results show that the accuracy rate of the proposed system achieved 97.45% for image datasets obtained freely from the internet, while 100% accuracy was obtained for image datasets collected with IP Cameras.
Keywords: Human activity recognition; video recording; Multilayer Perceptron
Abstrak
Kemajuan teknologi memungkinkan kegiatan pengawasan terhadap lingkungan menjadi lebih mudah yaitu dengan melakukan pemasangan peralatan rekam yang dapat ditempatkan pada lokasi-lokasi strategis tertentu. Keberadaan peralatan teknologi ini juga membawa perubahan dalam proses analisis terhadap rekaman video maupun gambar yang telah didapatkan. Proses pengolahan terhadap video rekaman tidak lagi menggunakan cara manual, namun dapat dilakukan secara otomatis dengan menggunakan teknologi pengolahan citra dan kecerdasan buatan. Berdasarkan rekaman video maupun gambar yang diperoleh, analisis dapat dilakukan untuk mengawasi keamanan lokasi, mencatat perubahan kondisi objek tertentu, mengenali aktivitas manusia pada saat tertentu, dan lain sebagainya. Makalah ini membahas pengembangan sebuah sistem pengenalan aktivitas manusia secara otomatis berdasarkan rekaman video menggunakan metode Multilayer Perceptron. Rekaman video sebelumnya akan dicacah menjadi kumpulan citra yang kemudian diproses dengan algoritma Multilayer Perceptron untuk proses pengenalannya. Luaran dari sistem aplikasi yang dirancang berupa pengenalan aktivitas yang dilakukan manusia pada waktu tertentu dan pencatatan aktivitas tersebut dalam sebuah log dengan timestamp tertentu. Dalam makalah ini, terdapat lima jenis aktivitas manusia yang dapat dikenali secara otomatis oleh sistem, yaitu mengangkat tangan, bertepuk tangan, berdiri, duduk, dan belajar. Hasil pengujian menunjukkan bahwa keberhasilan pendeteksian aktivitas manusia dengan metode Multilayer Perceptron memiliki tingkat akurasi 97.45% untuk dataset citra yang diperoleh secara bebas dari internet, sedangkan untuk dataset citra yang dikumpulkan dengan IP Camera memiliki tingkat akurasi sebesar 100%.
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