Update README.md

README.md

@@ -165,3 +165,36 @@ These issues highlight areas where the model could be improved with more diverse
 ### Known Failure Cases
 <img alt= "Failure Cases" src="https://huggingface.co/cvtechniques/VideoGameHandGestures/resolve/main/failure_cases.png" width="1100" height="700"></img>
 The model struggled with some of the photos from the RPS dataset as these images contain complex backgrounds, partially occluded hands, or ambiguous gestures. 
+
+### Data Biases
+Potential biases include:
+* limited subject diversity
+* similar backgrounds across many images
+* dataset partially composed of stock imagery
+* limited environmental variability
+
+### Environmental Limitations
+Model performance may degrade when:
+* lighting conditions vary significantly
+* gestures are performed at unusual angles
+* hands are partially occluded
+* gestures appear at extreme scales or distances
+
+### Inappropriate Use Cases
+This model should not be used for:
+* complex gesture recognition (complex 3D control schemes)
+* sign language recognition
+* high-precision human-computer interaction systems
+* any safety-critical applications
+
+### Sample Size Limitations
+The dataset is relatively small for object detection training, which may limit generalization to new users or environments.
+Future improvements would to the model would likely be a larger and more diverse dataset. Best course of action would be to remove stock images dataset and culminate gesture videos using diverse individuals, backgrounds, etc.
+***
+# Future Work
+Potential improvements include:
+* collecting a larger and more diverse gesture dataset
+* increasing the number of gesture classes
+* improving image quality and environmental diversity
+* exploring hand keypoint detection models instead of object detection
+* Keypoint estimation could allow detection of more complex hand gestures and improve gesture recognition accuracy.