scholarly journals Flipping food during grilling tasks, a dataset of utensils kinematics and dynamics, food pose and subject gaze

2022 ◽  
Vol 9 (1) ◽  
Author(s):  
Débora Pereira ◽  
Yuri De Pra ◽  
Emidio Tiberi ◽  
Vito Monaco ◽  
Paolo Dario ◽  
...  

AbstractThis paper presents a multivariate dataset of 2866 food flipping movements, performed by 4 chefs and 5 home cooks, with different grilled food and two utensils (spatula and tweezers). The 3D trajectories of strategic points in the utensils were tracked using optoelectronic motion capture. The pinching force of the tweezers, the bending force and torsion torque of the spatula were also recorded, as well as videos and the subject gaze. These data were collected using a custom experimental setup that allowed the execution of flipping movements with freshly cooked food, without having the sensors near the dangerous cooking area. Complementary, the 2D position of food was computed from the videos. The action of flipping food is, indeed, gaining the attention of both researchers and manufacturers of foodservice technology. The reported dataset contains valuable measurements (1) to characterize and model flipping movements as performed by humans, (2) to develop bio-inspired methods to control a cooking robot, or (3) to study new algorithms for human actions recognition.

2018 ◽  
Vol 168 (1) ◽  
pp. 81-92 ◽  
Author(s):  
Emily van der Nagel

Within the emerging field of critical algorithm studies, this article theorises that forced connections happen when algorithms exacerbate human actions in connecting otherwise disparate data points on digitally networked platforms to the subject of the data’s detriment. Although social media users may not have a comprehensive understanding of how algorithms work to make some content visible, when users form their own explanatory theories about these algorithms, they often intervene in these connections. Drawing on Michel de Certeau’s notion of strategies as the manipulations in which platforms engage to profile and control their users, and tactics as everyday acts of resistance, this article investigates two tactics within algorithmic cultures – Voldemorting, or not mentioning words or names in order to avoid a forced connection; and screenshotting, or making content visible without sending its website traffic – to demonstrate users’ understandings of the algorithms that seek to connect individuals to other people, platforms, content and advertisers, and their efforts to wrest back control.


2008 ◽  
Vol 20 (2) ◽  
pp. 322-331 ◽  
Author(s):  
Katsu Yamane ◽  
◽  
Daisuke Fukuda ◽  
Yoshihiko Nakamura

We present a markerless motion capture system able to determine the kinematic structure while measuring joint movement. In addition to volume data, we also use texture data to precisely measure the degrees of freedom that do not affect the shape, e.g., pronation/supination angles of the forearm and shank. We first obtain topology using a Reeb graph and independently build a tentative articulated-body chain model of the subject for each frame. We then extract a common optimized chain model by comparing joint angles of tentative models of all frames to identify which joints are related to describing the movement of the subject. Our system thus measures movement without prior knowledge of the structure. The system identifies the link length of objects with known structures based on measured data.


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