video
This dataset contains a diverse range of file types, including text, images, and audio, designed for multi-modal analysis and research. It includes text files (txt) with both structured and unstructured data, suitable for natural language processing tasks such as sentiment analysis and text classification. The image files cover various subjects and are intended for computer vision tasks like object detection and classification. Additionally, the dataset includes audio files in formats like MP3 and WAV, supporting speech recognition and sound analysis.
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16 Views
The DARai dataset is a comprehensive multimodal multi-view collection designed to capture daily activities in diverse indoor environments. This dataset incorporates 20 heterogeneous modalities, including environmental sensors, biomechanical measures, and physiological signals, providing a detailed view of human interactions with their surroundings. The recorded activities cover a wide range, such as office work, household chores, personal care, and leisure activities, all set within realistic contexts.
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686 Views
ATTENTION: THIS DATASET DOES NOT HOST ANY SOURCE VIDEOS. WE PROVIDE ONLY HIDDEN FEATURES GENERATED BY PRE-TRAINED DEEP MODELS AS DATA
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6536 Views
This is a dataset of 32 five-second-long vibration recordings. One human used a metal tool to perform one of two tool-mediated surface interactions (tapping or dragging) on the following four different surfaces: sandpaper (hard and rough), acrylic plastic (hard and smooth), rough paper (soft and rough), and rubber (soft and smooth). Each of the eight combinations of interaction and surface were recorded four times.
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422 Views
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273 Views
The image displays four segments of gestures from our dataset.
(a) The video sequence of rotating the wrist down and up as a signal for starting a new gesture.
(b)–(d) Three gestures samples (the triangle, letter b, and letter Z) taken from three different subjects at three different scenes (sitting at a desk, standing indoors, and standing outdoors.). The trajectory of each gesture canbe recognized from the movement of the background objects.
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367 Views