Datasets:
Languages:
English
Size:
1K<n<10K
Tags:
fall-detection
pose-estimation
posture-classification
elderly-care
mediapipe
human-activity-recognition
License:
File size: 10,589 Bytes
d48ce1e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 | # Kaggle column descriptions - copy/paste reference
For each group below, open every listed file's "Column descriptions" editor on the Kaggle dataset page and paste in the same column/description text.
## Label files (start_time / end_time / action / is_fall)
**Files:**
- `train/labels/hr_fall_detection_1.csv`
- `train/labels/hr_fall_detection_2.csv`
- `train/labels/hr_fall_detection_3.csv`
- `valid/labels/fall_detection_4.csv`
- `valid/labels/fall_detection_5.csv`
- `valid/labels/fall_detection_6.csv`
- `valid/labels/fall_detection_7.csv`
- `valid/labels/fall_detection_8.csv`
- `valid/labels/fall_detection_9.csv`
- `valid/labels/fall_detection_10.csv`
**Columns:**
- `start_time` (integer): Start of the labelled segment, in seconds from the start of the video.
- `end_time` (integer): End of the labelled segment, in seconds from the start of the video.
- `action` (string): Activity/posture label for this segment (e.g. Stand, Sit, Lie). A hyphenated value (e.g. Stand-Sit) marks a transition between two states. Blank means no activity was assigned yet (e.g. before the subject enters frame).
- `is_fall` (boolean): Whether this segment is labelled as a fall event.
## Static-pose feature files (un-predicted)
**Files:**
- `train/pose-1st-iteration/features_output.csv`
- `train/pose/features_output.csv`
- `train/pose/model1_features_output.csv`
- `train/pose/model2_features_output.csv`
**Columns:**
- `image_name` (string): Source static-pose image file name.
- `is_upright` (boolean): Whether the shoulder line is rotated enough relative to the hip line to indicate an upright torso (part of the standing-vs-lying rule).
- `percent_upright` (numeric): Confidence percentage backing the is_upright classification.
- `stand_left` (string): Left-leg standing classification from hip-knee-ankle bone-length geometry: standing, non_standing, squat, or uncertain_standing/uncertain_squat.
- `stand_right` (string): Right-leg equivalent of stand_left.
- `percent_stand_left` (numeric): Confidence percentage backing the stand_left classification.
- `percent_stand_right` (numeric): Confidence percentage backing the stand_right classification.
- `sit_left` (string): Left-leg sitting classification: sitting, non_sitting, or uncertain_sitting.
- `sit_right` (string): Right-leg equivalent of sit_left.
- `percent_sit_left` (numeric): Confidence percentage backing the sit_left classification.
- `percent_sit_right` (numeric): Confidence percentage backing the sit_right classification.
- `lie_left` (string): Left-side lying classification: lying or non_lying.
- `lie_right` (string): Right-side equivalent of lie_left.
## Static-pose feature files (predicted)
**Files:**
- `train/pose-1st-iteration/features_output_predicted.csv`
- `train/pose/features_output_predicted.csv`
- `train/pose/model1_features_output_predicted.csv`
- `train/pose/model2_features_output_predicted.csv`
**Columns:**
- `image_name` (string): Source static-pose image file name.
- `is_upright` (boolean): Whether the shoulder line is rotated enough relative to the hip line to indicate an upright torso (part of the standing-vs-lying rule).
- `percent_upright` (numeric): Confidence percentage backing the is_upright classification.
- `stand_left` (string): Left-leg standing classification from hip-knee-ankle bone-length geometry: standing, non_standing, squat, or uncertain_standing/uncertain_squat.
- `stand_right` (string): Right-leg equivalent of stand_left.
- `percent_stand_left` (numeric): Confidence percentage backing the stand_left classification.
- `percent_stand_right` (numeric): Confidence percentage backing the stand_right classification.
- `sit_left` (string): Left-leg sitting classification: sitting, non_sitting, or uncertain_sitting.
- `sit_right` (string): Right-leg equivalent of sit_left.
- `percent_sit_left` (numeric): Confidence percentage backing the sit_left classification.
- `percent_sit_right` (numeric): Confidence percentage backing the sit_right classification.
- `lie_left` (string): Left-side lying classification: lying or non_lying.
- `lie_right` (string): Right-side equivalent of lie_left.
- `label` (string): Ground-truth static posture (stand, sit, lie, bend, squat, etc.), parsed from the image filename.
- `predicted_label` (string): The package's rule-based static-posture prediction for this image. Blank where MediaPipe failed to detect any landmarks (this happens on some lying/occluded poses).
## K-means aspect-ratio cluster summary
**Files:**
- `train/pose/grouped_kmeans_static_pose_boundingbox_data.csv`
**Columns:**
- `aspect_ratio` (numeric): Minimum bounding-box aspect ratio within this K-means cluster. NOTE: this file is a pandas multi-index aggregation (groupby(...).agg(['min','max','mean','count'])) exported with duplicate-suffixed column names; row 0 of the data holds the literal sub-column labels ('min','max','mean','count') rather than a value - skip row 0 when loading, or treat it as a second header row.
- `aspect_ratio.1` (numeric): Maximum bounding-box aspect ratio within this K-means cluster (see column 'aspect_ratio' note about row 0).
- `aspect_ratio.2` (numeric): Mean bounding-box aspect ratio within this K-means cluster (see column 'aspect_ratio' note about row 0).
- `aspect_ratio.3` (numeric): Number of images in this K-means cluster (see column 'aspect_ratio' note about row 0).
## Overall bounding-box summary
**Files:**
- `train/pose/grouped_static_pose_boundingbox_data.csv`
**Columns:**
- `aspect_ratio` (numeric): Mean bounding-box aspect ratio across all 113 static pose images. NOTE: same pandas multi-index export artifact as grouped_kmeans_static_pose_boundingbox_data.csv - row 0 of the data holds the literal sub-column label ('mean') rather than a value.
- `relative_width` (numeric): Mean bounding-box width as a fraction of frame width, across all 113 images (see 'aspect_ratio' column note about row 0).
- `relative_height` (numeric): Mean bounding-box height as a fraction of frame height, across all 113 images (see 'aspect_ratio' column note about row 0).
## Bounding-box geometry (focused keypoints)
**Files:**
- `train/pose/static_pose_boundingbox_data.csv`
**Columns:**
- `image_name` (string): Source static-pose image file name.
- `frame_width` (integer): Source image width, in pixels.
- `frame_height` (integer): Source image height, in pixels.
- `aspect_ratio` (numeric): Height/width ratio of the MediaPipe pose bounding box.
- `relative_width` (numeric): Bounding box width as a fraction of the frame width.
- `relative_height` (numeric): Bounding box height as a fraction of the frame height.
## Bounding-box geometry (all 33 keypoints)
**Files:**
- `train/pose/static_pose_boundingbox_data_all_keypoints.csv`
**Columns:**
- `image_name` (string): Source static-pose image file name.
- `frame_width` (integer): Source image width, in pixels.
- `frame_height` (integer): Source image height, in pixels.
- `aspect_ratio` (numeric): Height/width ratio of the MediaPipe pose bounding box.
- `relative_width` (numeric): Bounding box width as a fraction of the frame width.
- `relative_height` (numeric): Bounding box height as a fraction of the frame height.
## Bounding-box geometry (with prediction)
**Files:**
- `train/pose/static_pose_boundingbox_data_bounding_box_size_predicted.csv`
**Columns:**
- `image_name` (string): Source static-pose image file name.
- `frame_width` (integer): Source image width, in pixels.
- `frame_height` (integer): Source image height, in pixels.
- `aspect_ratio` (numeric): Height/width ratio of the MediaPipe pose bounding box.
- `relative_width` (numeric): Bounding box width as a fraction of the frame width.
- `relative_height` (numeric): Bounding box height as a fraction of the frame height.
- `label` (string): Ground-truth static posture, parsed from the image filename.
- `predicted_label` (string): Posture prediction from a bounding-box-aspect-ratio-only classifier - an alternative to the landmark-angle-based classifier, useful when MediaPipe landmark detection itself fails (e.g. on occluded or lying poses).
## Per-frame video results
**Files:**
- `train/results of static pose classifier on training videos/hr_fall_detection_static_pose_class_on_video_1_results.csv`
- `train/results of static pose classifier on training videos/hr_fall_detection_static_pose_class_on_video_2_results.csv`
- `train/results of static pose classifier on training videos/hr_fall_detection_static_pose_class_on_video_3_results.csv`
**Columns:**
- `file_name` (integer): Frame index within the source video.
- `max_value` (numeric): Peak frame-differencing magnitude used to flag motion at this frame.
- `process_image` (boolean): Whether this frame was selected for pose estimation. Frames are motion-triggered rather than exhaustively sampled, so not every frame is processed.
- `label` (string): Ground-truth posture for this frame, derived from the manual activity-label CSV for the matching video and timestamp.
- `prediction` (string): The package's rule-based static-posture prediction for this frame. Blank where the frame was not processed or no pose was detected.
- `image_name` (string): Unused in this per-frame file (carried over from the shared feature-extraction function); always blank.
- `is_upright` (boolean): Whether the shoulder line is rotated enough relative to the hip line to indicate an upright torso (part of the standing-vs-lying rule).
- `percent_upright` (numeric): Confidence percentage backing the is_upright classification.
- `stand_left` (string): Left-leg standing classification from hip-knee-ankle bone-length geometry: standing, non_standing, squat, or uncertain_standing/uncertain_squat.
- `stand_right` (string): Right-leg equivalent of stand_left.
- `percent_stand_left` (numeric): Confidence percentage backing the stand_left classification.
- `percent_stand_right` (numeric): Confidence percentage backing the stand_right classification.
- `sit_left` (string): Left-leg sitting classification: sitting, non_sitting, or uncertain_sitting.
- `sit_right` (string): Right-leg equivalent of sit_left.
- `percent_sit_left` (numeric): Confidence percentage backing the sit_left classification.
- `percent_sit_right` (numeric): Confidence percentage backing the sit_right classification.
- `lie_left` (string): Left-side lying classification: lying or non_lying.
- `lie_right` (string): Right-side equivalent of lie_left.
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