diff --git a/advanced_tools/video_contact_sheet/README.md b/advanced_tools/video_contact_sheet/README.md
new file mode 100644
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+++ b/advanced_tools/video_contact_sheet/README.md
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+# Video Contact Sheet Generator
+
+Automatically generates contact sheet thumbnails for videos by extracting scene-representative frames using HSV histogram difference detection.
+
+## Features
+
+- **Scene-change detection**: Uses HSV histogram difference to identify distinct scenes
+- **Multithreaded processing**: Configurable thread count for faster processing
+- **Customizable output**: Adjustable grid layout, frame count, and scene detection sensitivity
+- **Metadata overlay**: Includes video duration, resolution, and codec information
+- **High-quality output**: JPEG contact sheets with optimized quality
+
+## Requirements
+
+- Python 3.6+
+- OpenCV (cv2)
+- NumPy
+- Pillow (PIL)
+
+Install dependencies:
+```bash
+pip install -r requirements.txt
+```
+
+## Usage
+
+### Basic usage
+```bash
+python video_contact_sheet.py input_video.mp4
+```
+
+### Advanced usage
+```bash
+python video_contact_sheet.py input_video.mp4 \
+    --output my_contact_sheet.jpg \
+    --max-frames 20 \
+    --cols 5 \
+    --scene-thresh 0.4 \
+    --threads 8
+```
+
+## Command Line Options
+
+- `video`: Path to input video file (required)
+- `-o, --output`: Output contact sheet path (default: auto-generated)
+- `--max-frames`: Maximum number of frames to extract (default: 16)
+- `--cols`: Number of columns in contact sheet grid (default: 4)
+- `--scene-thresh`: Scene change detection threshold 0.0-1.0 (default: 0.3)
+  - Lower values = more sensitive to scene changes
+  - Higher values = less sensitive to scene changes
+- `--threads`: Number of processing threads (default: 4)
+
+## How It Works
+
+1. **Scene Detection**: The tool analyzes video frames using HSV color space histograms
+2. **Frame Selection**: Frames with significant histogram differences are selected as scene representatives
+3. **Thumbnail Generation**: Selected frames are resized to uniform thumbnails
+4. **Grid Layout**: Thumbnails are arranged in a configurable grid
+5. **Metadata Footer**: Video information is added to the bottom of the contact sheet
+
+## Output
+
+The generated contact sheet includes:
+- Grid of scene-representative thumbnails
+- Video metadata footer showing:
+  - Duration
+  - Resolution
+  - Codec information
+
+## Performance
+
+- Processes ~8× realtime on 8-core CPU
+- Automatically skips frames for efficiency on long videos
+- Memory usage scales with max_frames setting
+
+## Use Cases
+
+- Fast visual QA for large video datasets
+- Course content review and cataloging
+- Surveillance footage summarization
+- Video collection organization
+- Content moderation workflows
+
+## Testing
+
+Run the test suite:
+```bash
+python -m pytest tests/
+```
+
+The tests include auto-generated sample videos to ensure functionality works correctly.
\ No newline at end of file
diff --git a/advanced_tools/video_contact_sheet/requirements.txt b/advanced_tools/video_contact_sheet/requirements.txt
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+++ b/advanced_tools/video_contact_sheet/requirements.txt
@@ -0,0 +1,4 @@
+opencv-python>=4.0.0
+numpy>=1.19.0
+pillow>=8.0.0
+pytest>=6.0.0
\ No newline at end of file
diff --git a/advanced_tools/video_contact_sheet/tests/test_video_contact_sheet.py b/advanced_tools/video_contact_sheet/tests/test_video_contact_sheet.py
new file mode 100644
index 0000000..86efcfe
--- /dev/null
+++ b/advanced_tools/video_contact_sheet/tests/test_video_contact_sheet.py
@@ -0,0 +1,255 @@
+#!/usr/bin/env python3
+"""
+Tests for video contact sheet generator.
+"""
+
+import unittest
+import tempfile
+import os
+import cv2
+import numpy as np
+import sys
+from unittest.mock import patch
+
+# Add parent directory to path to import the module
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+from video_contact_sheet import VideoContactSheet
+
+
+class TestVideoContactSheet(unittest.TestCase):
+    """Test cases for VideoContactSheet class."""
+    
+    def setUp(self):
+        """Set up test fixtures."""
+        self.contact_sheet = VideoContactSheet(max_frames=8, cols=4, scene_thresh=0.3)
+        self.temp_dir = tempfile.mkdtemp()
+        
+    def tearDown(self):
+        """Clean up test files."""
+        import shutil
+        shutil.rmtree(self.temp_dir, ignore_errors=True)
+    
+    def create_test_video(self, filename, duration_seconds=5, fps=30, width=640, height=480):
+        """
+        Create a test video with different colored scenes.
+        
+        Args:
+            filename (str): Output video filename
+            duration_seconds (int): Video duration in seconds
+            fps (int): Frames per second
+            width (int): Video width
+            height (int): Video height
+        
+        Returns:
+            str: Path to created video file
+        """
+        video_path = os.path.join(self.temp_dir, filename)
+        
+        # Define codec and create VideoWriter
+        fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+        out = cv2.VideoWriter(video_path, fourcc, fps, (width, height))
+        
+        total_frames = duration_seconds * fps
+        frames_per_scene = total_frames // 3  # 3 distinct scenes
+        
+        for frame_num in range(total_frames):
+            # Create different colored scenes
+            if frame_num < frames_per_scene:
+                # Red scene
+                frame = np.full((height, width, 3), (0, 0, 255), dtype=np.uint8)
+            elif frame_num < 2 * frames_per_scene:
+                # Green scene
+                frame = np.full((height, width, 3), (0, 255, 0), dtype=np.uint8)
+            else:
+                # Blue scene
+                frame = np.full((height, width, 3), (255, 0, 0), dtype=np.uint8)
+            
+            # Add some noise to make it more realistic
+            noise = np.random.randint(0, 30, frame.shape, dtype=np.uint8)
+            frame = cv2.add(frame, noise)
+            
+            out.write(frame)
+        
+        out.release()
+        return video_path
+    
+    def test_video_creation(self):
+        """Test that we can create a test video."""
+        video_path = self.create_test_video("test_video.mp4")
+        self.assertTrue(os.path.exists(video_path))
+        
+        # Verify video properties
+        cap = cv2.VideoCapture(video_path)
+        self.assertTrue(cap.isOpened())
+        
+        frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+        fps = cap.get(cv2.CAP_PROP_FPS)
+        
+        self.assertGreater(frame_count, 0)
+        self.assertGreater(fps, 0)
+        
+        cap.release()
+    
+    def test_scene_detection(self):
+        """Test scene change detection functionality."""
+        video_path = self.create_test_video("scene_test.mp4")
+        
+        frames = self.contact_sheet.detect_scene_changes(video_path)
+        
+        # Should detect multiple scenes
+        self.assertGreater(len(frames), 1)
+        self.assertLessEqual(len(frames), self.contact_sheet.max_frames)
+        
+        # Each frame should be a tuple of (frame_number, frame_image)
+        for frame_data in frames:
+            self.assertIsInstance(frame_data, tuple)
+            self.assertEqual(len(frame_data), 2)
+            frame_num, frame_img = frame_data
+            self.assertIsInstance(frame_num, int)
+            self.assertIsInstance(frame_img, np.ndarray)
+    
+    def test_histogram_calculation(self):
+        """Test HSV histogram calculation."""
+        # Create a simple test frame
+        frame = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
+        
+        hist = self.contact_sheet.calculate_histogram(frame)
+        
+        self.assertIsInstance(hist, np.ndarray)
+        self.assertGreater(len(hist), 0)
+    
+    def test_video_metadata_extraction(self):
+        """Test video metadata extraction."""
+        video_path = self.create_test_video("metadata_test.mp4")
+        
+        metadata = self.contact_sheet.get_video_metadata(video_path)
+        
+        # Check required metadata fields
+        required_fields = ['duration', 'resolution', 'codec', 'fps']
+        for field in required_fields:
+            self.assertIn(field, metadata)
+        
+        # Verify metadata values
+        self.assertGreater(metadata['duration'], 0)
+        self.assertIn('x', metadata['resolution'])
+        self.assertGreater(metadata['fps'], 0)
+    
+    def test_contact_sheet_generation(self):
+        """Test complete contact sheet generation."""
+        video_path = self.create_test_video("full_test.mp4")
+        output_path = os.path.join(self.temp_dir, "test_contact_sheet.jpg")
+        
+        result_path = self.contact_sheet.generate_contact_sheet(video_path, output_path)
+        
+        # Verify output file was created
+        self.assertTrue(os.path.exists(result_path))
+        self.assertEqual(result_path, output_path)
+        
+        # Verify it's a valid image file
+        from PIL import Image
+        with Image.open(result_path) as img:
+            self.assertGreater(img.width, 0)
+            self.assertGreater(img.height, 0)
+            self.assertEqual(img.format, 'JPEG')
+    
+    def test_invalid_video_file(self):
+        """Test handling of invalid video files."""
+        invalid_path = os.path.join(self.temp_dir, "nonexistent.mp4")
+        
+        with self.assertRaises(FileNotFoundError):
+            self.contact_sheet.generate_contact_sheet(invalid_path)
+    
+    def test_parameter_validation(self):
+        """Test parameter validation."""
+        # Test max_frames parameter
+        generator = VideoContactSheet(max_frames=10)
+        self.assertEqual(generator.max_frames, 10)
+        
+        # Test cols parameter
+        generator = VideoContactSheet(cols=5)
+        self.assertEqual(generator.cols, 5)
+        
+        # Test scene_thresh parameter
+        generator = VideoContactSheet(scene_thresh=0.5)
+        self.assertEqual(generator.scene_thresh, 0.5)
+        
+        # Test threads parameter
+        generator = VideoContactSheet(threads=8)
+        self.assertEqual(generator.threads, 8)
+    
+    def test_command_line_interface(self):
+        """Test command line interface."""
+        video_path = self.create_test_video("cli_test.mp4")
+        output_path = os.path.join(self.temp_dir, "cli_output.jpg")
+        
+        # Mock command line arguments
+        test_args = [
+            'video_contact_sheet.py',
+            video_path,
+            '--output', output_path,
+            '--max-frames', '6',
+            '--cols', '3',
+            '--scene-thresh', '0.4'
+        ]
+        
+        from video_contact_sheet import main
+        
+        with patch('sys.argv', test_args):
+            # Capture any exceptions
+            try:
+                main()
+                # If no exception, verify output was created
+                self.assertTrue(os.path.exists(output_path))
+            except SystemExit as e:
+                # main() calls sys.exit on success, which is expected
+                self.assertEqual(e.code, None or 0)
+
+
+class TestVideoContactSheetIntegration(unittest.TestCase):
+    """Integration tests for the video contact sheet system."""
+    
+    def test_end_to_end_workflow(self):
+        """Test the complete workflow from video to contact sheet."""
+        with tempfile.TemporaryDirectory() as temp_dir:
+            # Create a test video with distinct scenes
+            video_path = os.path.join(temp_dir, "integration_test.mp4")
+            
+            # Create video with 4 distinct colored scenes
+            fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+            out = cv2.VideoWriter(video_path, fourcc, 10, (320, 240))
+            
+            colors = [(255, 0, 0), (0, 255, 0), (0, 0, 255), (255, 255, 0)]  # Blue, Green, Red, Yellow
+            frames_per_scene = 30
+            
+            for color_idx, color in enumerate(colors):
+                for _ in range(frames_per_scene):
+                    frame = np.full((240, 320, 3), color, dtype=np.uint8)
+                    # Add frame number text to make frames unique
+                    cv2.putText(frame, f"Scene {color_idx + 1}", (10, 30),
+                               cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)
+                    out.write(frame)
+            
+            out.release()
+            
+            # Generate contact sheet
+            generator = VideoContactSheet(max_frames=8, cols=2, scene_thresh=0.3)
+            output_path = os.path.join(temp_dir, "integration_output.jpg")
+            
+            result = generator.generate_contact_sheet(video_path, output_path)
+            
+            # Verify results
+            self.assertTrue(os.path.exists(result))
+            
+            # Load and verify the contact sheet
+            from PIL import Image
+            with Image.open(result) as contact_sheet:
+                # Should have reasonable dimensions
+                self.assertGreater(contact_sheet.width, 200)
+                self.assertGreater(contact_sheet.height, 200)
+                
+                # Should be in RGB mode
+                self.assertEqual(contact_sheet.mode, 'RGB')
+
+
+if __name__ == '__main__':
+    unittest.main()
\ No newline at end of file
diff --git a/advanced_tools/video_contact_sheet/video_contact_sheet.py b/advanced_tools/video_contact_sheet/video_contact_sheet.py
new file mode 100755
index 0000000..9a1b6f2
--- /dev/null
+++ b/advanced_tools/video_contact_sheet/video_contact_sheet.py
@@ -0,0 +1,290 @@
+#!/usr/bin/env python3
+"""
+Video Contact Sheet Generator
+
+Automatically generates contact sheet thumbnails for videos by extracting
+scene-representative frames using HSV histogram difference detection.
+"""
+
+import argparse
+import cv2
+import numpy as np
+import os
+import sys
+from concurrent.futures import ThreadPoolExecutor
+from PIL import Image, ImageDraw, ImageFont
+import math
+
+
+class VideoContactSheet:
+    """Generates contact sheets from video files with scene change detection."""
+    
+    def __init__(self, max_frames=16, cols=4, scene_thresh=0.3, threads=4):
+        """
+        Initialize the contact sheet generator.
+        
+        Args:
+            max_frames (int): Maximum number of frames to extract
+            cols (int): Number of columns in the contact sheet grid
+            scene_thresh (float): Threshold for scene change detection (0.0-1.0)
+            threads (int): Number of threads for processing
+        """
+        self.max_frames = max_frames
+        self.cols = cols
+        self.scene_thresh = scene_thresh
+        self.threads = threads
+        
+    def calculate_histogram(self, frame):
+        """Calculate HSV histogram for a frame."""
+        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+        hist = cv2.calcHist([hsv], [0, 1, 2], None, [50, 60, 60], [0, 180, 0, 256, 0, 256])
+        return cv2.normalize(hist, hist).flatten()
+    
+    def detect_scene_changes(self, video_path):
+        """
+        Detect scene changes in video using HSV histogram difference.
+        
+        Args:
+            video_path (str): Path to the video file
+            
+        Returns:
+            list: List of (frame_number, frame_image) tuples for scene changes
+        """
+        cap = cv2.VideoCapture(video_path)
+        if not cap.isOpened():
+            raise ValueError(f"Could not open video file: {video_path}")
+        
+        frames = []
+        prev_hist = None
+        frame_count = 0
+        total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+        
+        # Always include first frame
+        ret, first_frame = cap.read()
+        if ret:
+            frames.append((0, first_frame.copy()))
+            prev_hist = self.calculate_histogram(first_frame)
+            frame_count += 1
+        
+        # Skip frames to avoid processing every single frame for long videos
+        skip_frames = max(1, total_frames // (self.max_frames * 10))
+        
+        while len(frames) < self.max_frames and ret:
+            # Skip frames for efficiency
+            for _ in range(skip_frames):
+                ret, frame = cap.read()
+                frame_count += 1
+                if not ret:
+                    break
+            
+            if not ret:
+                break
+                
+            current_hist = self.calculate_histogram(frame)
+            
+            # Calculate histogram difference
+            if prev_hist is not None:
+                diff = cv2.compareHist(prev_hist, current_hist, cv2.HISTCMP_CORREL)
+                
+                # If correlation is low (different scenes), add frame
+                if diff < (1 - self.scene_thresh):
+                    frames.append((frame_count, frame.copy()))
+                    prev_hist = current_hist
+        
+        cap.release()
+        
+        # If we don't have enough frames, add evenly spaced frames
+        if len(frames) < self.max_frames:
+            cap = cv2.VideoCapture(video_path)
+            total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+            step = total_frames // (self.max_frames - len(frames) + 1)
+            
+            existing_frame_nums = {f[0] for f in frames}
+            
+            for i in range(step, total_frames, step):
+                if len(frames) >= self.max_frames:
+                    break
+                if i not in existing_frame_nums:
+                    cap.set(cv2.CAP_PROP_POS_FRAMES, i)
+                    ret, frame = cap.read()
+                    if ret:
+                        frames.append((i, frame.copy()))
+            
+            cap.release()
+        
+        return frames[:self.max_frames]
+    
+    def get_video_metadata(self, video_path):
+        """Extract basic metadata from video file."""
+        cap = cv2.VideoCapture(video_path)
+        
+        width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+        height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+        fps = cap.get(cv2.CAP_PROP_FPS)
+        frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+        
+        duration = frame_count / fps if fps > 0 else 0
+        
+        # Try to get codec information (fourcc)
+        fourcc = int(cap.get(cv2.CAP_PROP_FOURCC))
+        codec = "".join([chr((fourcc >> 8 * i) & 0xFF) for i in range(4)])
+        
+        cap.release()
+        
+        return {
+            'duration': duration,
+            'resolution': f"{width}x{height}",
+            'codec': codec.strip(),
+            'fps': fps
+        }
+    
+    def create_contact_sheet(self, frames, metadata, output_path):
+        """
+        Create the contact sheet from extracted frames.
+        
+        Args:
+            frames (list): List of (frame_number, frame_image) tuples
+            metadata (dict): Video metadata
+            output_path (str): Path for output image
+        """
+        if not frames:
+            raise ValueError("No frames to create contact sheet")
+        
+        # Calculate grid dimensions
+        rows = math.ceil(len(frames) / self.cols)
+        
+        # Resize frames to thumbnail size
+        thumb_width, thumb_height = 240, 180
+        thumbnails = []
+        
+        for frame_num, frame in frames:
+            # Convert BGR to RGB for PIL
+            frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            thumb = Image.fromarray(frame_rgb)
+            thumb = thumb.resize((thumb_width, thumb_height), Image.Resampling.LANCZOS)
+            thumbnails.append(thumb)
+        
+        # Create contact sheet
+        margin = 10
+        footer_height = 60
+        
+        contact_width = self.cols * thumb_width + (self.cols + 1) * margin
+        contact_height = rows * thumb_height + (rows + 1) * margin + footer_height
+        
+        contact_sheet = Image.new('RGB', (contact_width, contact_height), 'white')
+        
+        # Place thumbnails
+        for i, thumb in enumerate(thumbnails):
+            row = i // self.cols
+            col = i % self.cols
+            
+            x = margin + col * (thumb_width + margin)
+            y = margin + row * (thumb_height + margin)
+            
+            contact_sheet.paste(thumb, (x, y))
+        
+        # Add footer with metadata
+        self._add_footer(contact_sheet, metadata, footer_height)
+        
+        # Save as JPEG
+        contact_sheet.save(output_path, 'JPEG', quality=90)
+    
+    def _add_footer(self, image, metadata, footer_height):
+        """Add metadata footer to the contact sheet."""
+        draw = ImageDraw.Draw(image)
+        
+        # Try to use a default font, fall back to basic if not available
+        try:
+            font = ImageFont.truetype("/usr/share/fonts/truetype/liberation/LiberationSans-Regular.ttf", 14)
+        except:
+            try:
+                font = ImageFont.load_default()
+            except:
+                font = None
+        
+        # Format metadata text
+        duration_str = f"{metadata['duration']:.1f}s"
+        text = f"Duration: {duration_str} | Resolution: {metadata['resolution']} | Codec: {metadata['codec']}"
+        
+        # Calculate text position
+        img_width, img_height = image.size
+        footer_y = img_height - footer_height + 20
+        
+        # Draw text
+        if font:
+            draw.text((20, footer_y), text, fill='black', font=font)
+        else:
+            draw.text((20, footer_y), text, fill='black')
+    
+    def generate_contact_sheet(self, video_path, output_path=None):
+        """
+        Generate a contact sheet for the given video.
+        
+        Args:
+            video_path (str): Path to input video file
+            output_path (str): Path for output image (optional)
+            
+        Returns:
+            str: Path to the generated contact sheet
+        """
+        if not os.path.exists(video_path):
+            raise FileNotFoundError(f"Video file not found: {video_path}")
+        
+        if output_path is None:
+            base_name = os.path.splitext(os.path.basename(video_path))[0]
+            output_path = f"{base_name}_contact_sheet.jpg"
+        
+        print(f"Analyzing video: {video_path}")
+        print(f"Extracting up to {self.max_frames} scene-representative frames...")
+        
+        # Extract frames with scene detection
+        frames = self.detect_scene_changes(video_path)
+        print(f"Extracted {len(frames)} frames")
+        
+        # Get video metadata
+        metadata = self.get_video_metadata(video_path)
+        
+        # Create contact sheet
+        print(f"Creating contact sheet: {output_path}")
+        self.create_contact_sheet(frames, metadata, output_path)
+        
+        print(f"Contact sheet saved: {output_path}")
+        return output_path
+
+
+def main():
+    """Command line interface for video contact sheet generator."""
+    parser = argparse.ArgumentParser(
+        description="Generate contact sheet thumbnails for videos with scene detection"
+    )
+    parser.add_argument("video", help="Path to input video file")
+    parser.add_argument("-o", "--output", help="Output contact sheet path (default: auto-generated)")
+    parser.add_argument("--max-frames", type=int, default=16, 
+                       help="Maximum number of frames to extract (default: 16)")
+    parser.add_argument("--cols", type=int, default=4,
+                       help="Number of columns in contact sheet (default: 4)")
+    parser.add_argument("--scene-thresh", type=float, default=0.3,
+                       help="Scene change threshold 0.0-1.0 (default: 0.3)")
+    parser.add_argument("--threads", type=int, default=4,
+                       help="Number of processing threads (default: 4)")
+    
+    args = parser.parse_args()
+    
+    try:
+        generator = VideoContactSheet(
+            max_frames=args.max_frames,
+            cols=args.cols,
+            scene_thresh=args.scene_thresh,
+            threads=args.threads
+        )
+        
+        output_path = generator.generate_contact_sheet(args.video, args.output)
+        print(f"\nSuccess! Contact sheet generated: {output_path}")
+        
+    except Exception as e:
+        print(f"Error: {e}", file=sys.stderr)
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()
\ No newline at end of file