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All Journal ComEngApp : Computer Engineering and Applications Journal Jurnal Buana Informatika Perfecting a Video Game with Game Metrics CommIT (Communication & Information Technology) International Journal of Advances in Intelligent Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Communications in Science and Technology IJITEE (International Journal of Information Technology and Electrical Engineering) Indonesian Journal of Electrical Engineering and Computer Science Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi)
Igi Ardiyanto
Universitas Gadjah Mada
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Transportation

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Journal : CommIT (Communication

 1 
Geometric Model for Human Body Orientation Classification Ardiyanto, Igi
CommIT (Communication and Information Technology) Journal Vol 9, No 1 (2015): CommIT Vol. 9 No. 1 Tahun 2015
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v9i1.1659

Abstract

This  paper proposes  an approach  for cal- culating  and estimating  human body orientation  using geometric model. A novel framework integrating gradient shape and texture model of the human body orientation is proposed.  The gradient  is a natural way for describing the human  shapes, while the texture  explains the body characteristic. The framework  is then combined with the random  forest classifier to obtain a robust  class  differ- ence  of the human body orientation. Experiments and comparison results are provided to show the advantages of our system over state-of-the-art. For both modeled and un-modeled gradient-texture  features with random forest classifier, they achieve the highest accuracy on separating each human orientation   class, respectively  56.9% and 67.3% for TUD-Stadtmitte  dataset.
Geometric Model for Human Body Orientation Classification Igi Ardiyanto
CommIT (Communication and Information Technology) Journal Vol. 9 No. 1 (2015): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v9i1.1659

Abstract

This  paper proposes  an approach  for cal- culating  and estimating  human body orientation  using geometric model. A novel framework integrating gradient shape and texture model of the human body orientation is proposed.  The gradient  is a natural way for describing the human  shapes, while the texture  explains the body characteristic. The framework  is then combined with the random  forest classifier to obtain a robust  class  differ- ence  of the human body orientation. Experiments and comparison results are provided to show the advantages of our system over state-of-the-art. For both modeled and un-modeled gradient-texture  features with random forest classifier, they achieve the highest accuracy on separating each human orientation   class, respectively  56.9% and 67.3% for TUD-Stadtmitte  dataset.
Co-Authors Adhistya Erna Permanasari Ahmad Fauzi Mabrur Ahmad Nasikun Aninditya Anggari Nuryono Chandra Ramadhan Atmaja Perdana Erwin Setyo Nugroho Hanung Adi Nugroho Hanung Adi Nugroho Hanung Adi Nugroho Luky Hidayat Made Rahmawaty, Made Muhammad Fawaz Saputra Nasikun, Ahmad Noor Akhmad Setiawan Nugroho, Arseto Satriyo Nurcahyani Wulandari Persada, Anugerah Galang Rezty Amalia Aras Rizky Naufal Perdana Rudy Hartanto Setialana, Pradana Silvester Tena Sulis Setiowati Sunu Wibirama Teguh Bharata Adji Tri Lestari Vesi Yulyanti Widhia KZ Oktoeberza Yuli Triyani