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"This book describes one of the first systems for sparse point-based 3D reconstruction and egomotion estimation from an image sequence; able to run in real-time at video frame rate and assuming quite weak prior knowledge about camera calibration, motion or scene. Its chapters unify the current perspectives of the robotics and computer vision communities on the 3D vision topic : as usual in robotics sensing, the explicit estimation and propagation of the uncertainty hold a central role in the sequential video processing and is shown to boost the efficiency and performance of the 3D estimation. On the other hand, some of the most relevant topics discussed in SfM by the computer vision scientists are addressed under this probabilistic filtering scheme, namely projective models, spurious rejection, model selection and self-calibration."

"[ABSTRAKPenelitian ini bertujuan untuk meneliti perubahan persepsi investor terhadap risiko berinvestasi di Indonesia. Pada penelitian ini, deret waktu dari parameter risk aversion diestimasi menggunakan indeks saham Indonesia menggunakan data imbal hasil dengan frekuensi harian dari tahun 1990 hingga tahun 2015. Penelitian ini menggunakan model AR(1)-GARCH(1,1)-M untuk mengestimasi parameter risk aversion pada pasar saham Indonesia. Pemodelan yang dilakukan pada penelitian ini memodelkan parameter risk aversion dalam proses random walk. Penemuan dari penelitian ini menunjukkan bahwa premi risiko memiliki variansi sepanjang waktu dan mengindikasikan bahwa pasar saham Indonesia berpengaruh terhadap situasi perekonomian global.

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ABSTRACTThe purpose of this thesis is to examine the change in perception of risk by investors in Indonesia. In this research, the time series of risk aversion parameter is estimated for the Indonesian stock market using daily return data from year 1990 to 2015. This research makes use of AR(1)-GARCH(1,1)-M model to estimate the risk aversion parameter for Indonesian stock market. The model used in this research modelled the risk aversion parameter to follow a random walk process. The findings of this thesis show that the risk premium varies over time and indicate that the Indonesian stock market is vulnerable to global economy, The purpose of this thesis is to examine the change in perception of risk by investors in Indonesia. In this research, the time series of risk aversion parameter is estimated for the Indonesian stock market using daily return data from year 1990 to 2015. This research makes use of AR(1)-GARCH(1,1)-M model to estimate the risk aversion parameter for Indonesian stock market. The model used in this research modelled the risk aversion parameter to follow a random walk process. The findings of this thesis show that the risk premium varies over time and indicate that the Indonesian stock market is vulnerable to global economy]"