A FACE & EYE DETECTION MODEL FOR DRIVING AN AUTOMOBILE

This paper proposes an inexpensive vision-based system to exactly identify Eyes Off target (EOR). The device has three primary components: 1) robust facial feature monitoring 2) mind pose and gaze estimation and 3) 3-D geometric reasoning to recognize EOR. Within the video stream from the camera put on the controls column, our physiques tracks facial features within the driver’s face. While using the supervised landmarks plus a 3-D face model, the device computes mind pose and gaze direction. Distracted driving is probably the primary causes of vehicle collisions within the United States. States. Passively monitoring a driver’s activities comprises the building blocks from the automobile safety system that could potentially reduce the quantity of accidents by estimating the driver’s focus of attention. Your brain pose estimation formula is robust to no rigid face deformations due to modifications in expressions. Finally, employing a 3-D geometric analysis, the device reliably detects EOR. The recommended system does not need any driver-dependent calibration or manual initialization and works instantly (25 FPS), during the day and night. Our physiques accomplished above 90% EOR precision for individuals examined situations. To validate the performance in the system in the real vehicle atmosphere, we transported out a comprehensive experimental evaluation under all types illumination conditions, facial expressions, and individuals

A 3D FACE MODEL FOR DRIVING AN AUTOMOBILE

This paper proposes an inexpensive vision-based system to exactly identify Eyes Off target (EOR). The device has three primary components: 1) robust facial feature monitoring 2) mind pose and gaze estimation and 3) 3-D geometric reasoning to recognize EOR. Within the video stream from the camera put on the controls column, our physiques tracks facial features within the driver’s face. While using the supervised landmarks plus a 3-D face model, the device computes mind pose and gaze direction. Distracted driving is probably the primary causes of vehicle collisions within the United States. States. Passively monitoring a driver’s activities comprises the building blocks from the automobile safety system that could potentially reduce the quantity of accidents by estimating the driver’s focus of attention. Your brain pose estimation formula is robust to no rigid face deformations due to modifications in expressions. Finally, employing a 3-D geometric analysis, the device reliably detects EOR. The recommended system does not need any driver-dependent calibration or manual initialization and works instantly (25 FPS), during the day and night. Our physiques accomplished above 90% EOR precision for individuals examined situations. To validate the performance in the system in the real vehicle atmosphere, we transported out a comprehensive experimental evaluation under all types illumination conditions, facial expressions, and individuals

Synergy-Based Hand Pose Sensing: Optimal Glove Design

In this paper we study the problem of improving human hand pose sensing device performance by exploiting the knowledge on how humans most frequently use their hands in grasping tasks. In a companion paper we studied the problem of maximizing the reconstruction accuracy of the hand pose from partial and noisy data provided by any given pose sensing device (a sensorized "glove") taking into account statistical a priori information. In this paper we consider the dual problem of how to design pose sensing devices, i.e. how and where to place sensors on a glove, to get maximum information about the actual hand posture. We study the continuous case, whereas individual sensing elements in the glove measure a linear combination of joint angles, the discrete case, whereas each measure corresponds to a single joint angle, and the most general hybrid case, whereas both continuous and discrete sensing elements are available. The objective is to provide, for given a priori information and fixed number of measurements, the optimal design minimizing in average the reconstruction error. Solutions relying on the geometrical synergy definition as well as gradient flow-based techniques are provided. Simulations of reconstruction performance show the effectiveness of the proposed optimal design.Comment: Submitted to International Journal of Robotics Research 201